WO2025011740A1

WO2025011740A1 - A heavy-duty vehicle motion support device interface format

Info

Publication number: WO2025011740A1
Application number: PCT/EP2023/068988
Authority: WO
Inventors: Johan Lindberg
Original assignee: Volvo Truck Corp
Current assignee: Volvo Truck Corp
Priority date: 2023-07-10
Filing date: 2023-07-10
Publication date: 2025-01-16
Anticipated expiration: 2026-01-10

Abstract

A computer-implemented control system (300, 310, 320, 500, 600) for controlling at least one motion support device, MSD, (530, 540, 550) on a heavy-duty vehicle (100), the computer- implemented control system comprising processing circuitry arranged to obtain a set of filter parameters that define a digital filter function associated with a capability of the MSD (530, 540, 550) as function of time, obtain a nominal MSD request signal indicative of a desired actuation by the MSD, process the nominal MSD request signal by the digital filter function into a capability limited MSD request signal, and control the at least one MSD based on the capability limited MSD request signal.

Description

A HEAVY-DUTY VEHICLE MOTION SUPPORT DEVICE INTERFACE FORMAT

TECHNICAL FIELD

This disclosure relates generally to control of heavy-duty vehicles such as trucks, buses, and heavy construction equipment. In particular aspects, the disclosure relates to a motion support device interface format that allows efficient representation of time-dependent capabilities of actuators such as brakes, propulsion devices, and other motion support devices on the vehicle.

Although the disclosure may be described with respect to a particular vehicle, the disclosure is not restricted to any particular vehicle or vehicle type.

BACKGROUND

A heavy-duty vehicle, such as a truck or a bus, often comprises a plurality of different motion support devices (MSD), i.e., actuators such as propulsion devices, steering actuators, active suspension systems and service brakes that can be used to control the motion of the vehicle.

An MSD may be associated with a time-dependent capability limitation, meaning that the amount of actuation possible to achieve using the MSD varies over time. A friction brake may for instance risk performance degradation due to brake fading if it is actuated at too high braking force for too long. An electric machine may be able to generate peak torque for a limited period of time, but will overheat if it is actuated at peak torque for too long.

This type of time-dependent actuator capability limitation is preferably taken into account when controlling the vehicle.

SUMMARY

The present disclosure relates generally to control systems and methods for control of MSDs in heavy-duty vehicles. Some of the techniques disclosed herein may be described in terms of a computer system and/or as methods performed by the computer system. There is disclosed a computer-implemented control system for controlling at least one MSD on a heavy-duty vehicle. The computer-implemented control system comprises processing circuitry arranged to obtain a set of filter parameters that define a digital filter function associated with a capability of the MSD as function of time, obtain a nominal MSD request signal indicative of a desired actuation by the MSD, process the nominal MSD request signal by the digital filter function into a capability limited MSD request signal, and control the at least one MSD based on the capability limited MSD request signal. The digital filter function represents the time-dependent capability limitation of the MSD, and can be used to generate a capability limited MSD request signal that does not exceed the time-dependent capability of the MSD, This way a time-dependent MSD capability can be efficiently incorporated into the control of the MSD. By representing the time-dependent MSD capability as a digital filter function, characterized, e.g., by a step response, more accurate control of the MSD can be achieved. In particular, some MSDs may be possible to utilize to a higher degree by representing the time-dependent capability limitation as a digital filter function.

According to some aspects, the digital filter function is a step response describing a decreasing MSD capability as function of time, in response to a step function nominal MSD request signal. The set of filter parameters may comprise a set of impulse response parameters, a reference capability level and a sampling time duration. The set of filter parameters are preferably given relative to a continuous limit level of the MSD.

According to some aspects, the processing circuitry is arranged to obtain the set of filter parameters at least in part from the MSD. This means that the MSD, or a control unit associated with the MSD, can communicate information about the time-dependent capabilities of the actuator to a higher layer control unit in an efficient manner. Thus, an efficient interface for communicating MSD capability is provided herein. The processing circuitry may also, at least in part, be arranged to obtain the set of filter parameters as a pre-stored set of filter parameters.

The processing circuitry is preferably arranged to obtain the set of filter parameters as a function of at least one other parameter, such as an operating temperature of the MSD, an actuator wear state, or some other parameter that has an effect on the capability of the MSD. This way the time-dependent capability of an MSD can be modulated in dependence of an influence of some other factor affecting the capability of the MSD. The techniques disclosed herein are particularly suitable for use in battery-electric vehicles, BEV. Hence, the MSD may be or at least comprise an electric machine and the at least one other parameter comprises a state of charge (SoC) of a battery system associated with the electric machine. The techniques disclosed herein are also applicable for control of propulsion devices, power steering systems, and friction brakes such as disc or drum brakes.

According to some aspects, the processing circuitry is arranged to process the nominal MSD request signal by filtering the nominal MSD request signal by the digital filter function to obtain the capability limited MSD request signal. This way of processing nominal MSD request signals preserves much of the information in the nominal MSD request signal, compared to the case where the nominal MSD request signal is simply truncated to satisfy a capability constraint.

The processing circuitry is preferably arranged to determine a difference signal as the difference between nominal MSD request signal and the capability limited MSD request signal, and to trigger an action in case the difference satisfies a pre-determined magnitude criterion. By monitoring the input and output to the digital filter function during filtering of the nominal MSD request signal, it becomes possible to reliably detect when an actuator is operating in saturated state, i.e., when the nominal MSD request signal breaches the capability limit of the MSD. This information can be used by higher layer control systems on the vehicle to adjust the control strategy of the vehicle. The power of the difference signal can be taken as a measure of how much the time-dependent capability is currently breached. The accumulated energy of the difference signal is indicative of how much the capability has been breached over a time period.

According to some aspects, the processing circuitry is arranged to process two or more capability limited MSD request signals into an aggregated capability limited MSD request signal. Thus, a joint capability limit of a sub-system comprising two or more MSDs can be obtained using the techniques described herein. The sub-system may, e.g., comprise a battery system and an electric machine.

The processing circuitry may furthermore be arranged to execute an MSD control allocation routine or MSD coordination function involving a plurality of MSDs, where a set of constraints associated with the control allocation routine are defined based on the set of filter parameters. This way the digital filter-based way of representing MSD capability constraints can be efficiently integrated into advanced control allocation methods as optimization constraints, which is an advantage. The MSD control allocation routine or MSD coordination function is preferably configured to solve a constrained optimization problem, where the constraints are determined based on the set of filter parameters. The MSD control allocation routine can also be configured to solve an optimization problem associated with one or more cost functions, where the cost functions are configured in dependence of any of; an energy expenditure of MSD actuators, a wear incurred on MSD actuators, and a passenger convenience metric.

The different techniques and features of the computer system discussed herein may also be described as corresponding methods, associated with the same advantages. The above aspects, accompanying claims, and/or examples disclosed herein above and later below may be suitably combined with each other as would be apparent to anyone of ordinary skill in the art.

Additional features and advantages are disclosed in the following description, claims, and drawings, and in part will be readily apparent therefrom to those skilled in the art or recognized by practicing the disclosure as described herein. There are also disclosed herein control units, computer systems, computer readable media, and computer program products associated with the above discussed technical benefits.

BRIEF DESCRIPTION OF THE DRAWINGS

With reference to the appended drawings, below follows a more detailed description of aspects of the disclosure cited as examples.

Figure 1 illustrates an example heavy-duty vehicle,

Figure 2 is a graph that schematically exemplifies MSD capability as function of time,

Figures 3A-C schematically illustrate MSD capability interfaces based on a filter parameter representation of MSD capability,

Figure 4 shows nominal and capability limited MSD request signals,

Figure 5 shows aspects of an example vehicle motion control system,

Figure 6 illustrates some example motion support devices on a heavy-duty vehicle, Figures 7A-B illustrate example MSD capability functions,

Figure 8 shows an example aggregated capability function,

Figure 9 is a schematic diagram of an exemplary computer system,

Figure 10 is a flow chart illustrating methods,

Figure 11 shows an example computer program product,

Figure 12 is a graph illustrating temperature increase in a device over time,

Figure 13 shows an example digital filter function, and

Figure 14 shows an example set of filter parameters.

DETAILED DESCRIPTION

The present disclosure will now be described more fully hereinafter with reference to the accompanying drawings, in which exemplary embodiments are shown. The disclosure may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided for thoroughness and completeness. Like reference character refer to like elements throughout the description. Aspects set forth below represent the necessary information to enable those skilled in the art to practice the disclosure.

Figure 1 illustrates an example heavy-duty vehicle 100, here in the form of a truck comprising a tractor 110 and a trailer 120. The tractor 110 of the vehicle 100 comprises two front wheels 101 of a steered front axle and a set of rear wheels 102 on two rear tractor axles. The trailer 120 also comprises wheels 103 that support it on the road surface 104. One or more tractor rear axles, and/or one or more trailers axles may also be steered axles.

A heavy-duty vehicle may be defined in some cases as a freight vehicle of more than 3.5 metric tons or as a passenger transport vehicles of more than 8 seats. A heavy-duty vehicle may also be defined as a vehicle with a frontal area that is larger than 45 square feet, which is about 4.18 square meters. The teachings herein are particularly suitable for use with semi-trailer type vehicles such as that shown in Figure 1 and rigid trucks, including rigid trucks with dollies and one or more trailers. The vehicle 100 comprises a computer-implemented control system that is arranged to estimate vehicle motion relative to the road surface 104 and/or in a global reference system. The control system implements one or more control functions that control vehicle motion based at least in part on the estimated vehicle motion. This control system may comprise one or more control units 130 distributed over the vehicle or centralized at one place. Each vehicle control unit 130 may comprise one or more processor devices. A processor device may be distributed over several spatially separated units or centralized in one place. The control system, or parts thereof, may be arranged to communicate via wireless link 140 to a wireless access point 150, such as a radio base station of a cellular access network or the like. Thus, the vehicle control system may communicate with one or more remote servers 160 implementing data repositories, remote processing resources, and the like, in order to exchange data and perform various computation tasks. The computer-implemented control system may be referred to as, or form part of, a system for vehicle motion management (VMM). A higher layer control system may use the VMM system to obtain a desired motion by the vehicle 100. The higher layer control system may be referred to as a traffic situation management (TSM) system, and may comprise any of a manual driver interface, advanced driver assistance (ADAS) functions, as well as autonomous drive (AD) capability.

Generally, herein, various forms of data signals and messages are transmitted between functions, internal to some processing circuitry or in between physically separated processing devices. These signals and messages are often referred to in terms of data indicative of a given parameter or data item. It is appreciated that the term “data indicative of’ is to be construed broadly to mean, e.g., the actual value, an approximation of the value, or an abstraction of the value. The data can for instance be represented using more or less bits in a digital message or transmitted in analog form. A given value may also be represented using an abstraction or code, such as a discrete value in a given predefined range.

A heavy-duty vehicle 100 comprises a number of actuators, referred to herein as motion support devices (MSD). The MSDs of a vehicle may comprise one or more combustion engines, electric machines, steering actuators, brake systems, active suspension systems, and so on. A heavy-duty vehicle, such as the vehicle 100, is normally over-actuated, which means that a given motion by the vehicle can be obtained by a number of different actuator motion request combinations. Steering can, for instance, be achieved by actuating a power steering system, and also by differential braking on the two sides of the vehicle. An active suspension system can also be used to obtain a certain curvature by the vehicle 100. A global motion request issued, e.g., by a driver or by an autonomous control system forming part of the TSM function of the vehicle 100, for a given overall vehicle motion behavior can therefore be satisfied in a number of different ways, some good and some not so good in terms of cost, where the cost function may involve aspects such as component wear, energy expenditure, and passenger convenience. Some vehicles may implement advanced control allocation routines or MSD coordination functions which coordinate the different MSDs on the vehicle to obtain a desired vehicle motion. One such example will be discussed below in connection to Figure 5.

An MSD, such as a friction brake used to generate braking torque, or an electric machine used to generate both propulsion and braking torque, or an energy source such as a battery system, is normally associated with a time dependent capability limit. An MSD capable of continuously supporting a given nominal level of actuation can often support higher magnitude actuation compared to the nominal level of actuation as long as the MSD request for the higher level of actuation is time limited. In other words, many MSDs are capable of strong actuation for short time periods and less strong actuation for more extended periods of time.

The capabilities of motion actuators and energy sources in a vehicle are typically defined as a maximum transient level limit for a short duration of time and in addition possibly a lower- level limitation for longer duration and then a continuous operation level limit, as illustrated by the diagram 200 in Figure 2. An electric machine may, e.g., often be capable of delivering peak torque for a short time duration, and a lower torque for an extended period of time. A battery system is also often capable of delivering a peak current for short duration of time, and a smaller current for more prolonged periods of time. With reference to Figure 2, an example MSD may be associated with a maximum limit, a short term limit, and a continuous limit, where the maximum limit can only be supported during a transient time duration, and the short term limit can be supported during a short time duration. The continuous limit can be supported indefinitely. This type of time-dependent capability limit defined using a relatively small number of constant levels associated with respective time periods in a “staircase” manner is a very course way to describe the actual time-dependent capability limit of most actuators. The combined capability of the different motion actuators and energy sources on the tractor 110 and the trailer 120 define the aggregated capability of the vehicle 100. The combined capability of the actuators and energy sources is typically defined as the combined minimum limit of all the MSD capability limitations, i.e., the combined capability is given as the smallest capability of the actuators and energy sources for each point in time.

Looking at the time dependent capability limitation function 200 exemplified in Figure 2, it is realized that the capability limitation of an MSD can be represented as a step function of a digital filter, i.e., the integration of a digital filter impulse response, relative to some reference level such as the maximum actuator capability level or the continuous capability level, measured in Newtons, Newton-meters, Watts, Amperes, in dependence of the type of MSD considered. In this way the capability limitation function of a general MSD device or system of devices can be interpreted as a signal processing filter function for the values exceeding the continuous limit or relative to some other reference actuation level. A digital filter is defined by its filter parameters, i.e., its transfer function, along with a sample time definition and reference level. Thus, the filter parameters can be identified by the corresponding impulse response of the capability limitation digital filter function. The impulse response can be calculated as the difference of the step response at a discrete time instance and the same step response at a previous discrete time instance.

In case the digital filter is defined as a discrete time digital filter, the filter tap values of a finite impulse response (FIR), or infinite impulse response (IIR) structure can be used to define the filter. The poles and zeros of the digital filter can also be used to define the digital filter. An example step response of a digital filter is illustrated in Figure 13. An example Bode diagram describing the transfer function of the digital filter in Figure 13 is illustrated in Figure 14.

By describing an MSD capability limitation as a digital filter function in this manner, a large variety of MSDs of different types can be handled in the same way, which is an advantage. The filter parameters for a given MSD can be continuously updated to keep the capability limitation information updated. By representing time-dependent capability of an MSD or a system of MSDs as a digital filter, i.e., by filter parameters that define the digital filtering function, an efficient representation of the time-dependent capability characteristics of an MSD or of a system of MSDs is obtained compared to if the time-dependent capability function had been communicated as a vector of values.

Another advantage associated with representing MSD capability limitation in this manner is that a nominal MSD request signal can be filtered by the digital filter function to obtain a capability limited MSD request signal. In this way the small signal behavior of the nominal MSD request signal is preserved even when the MSD is operating in limitation, as will be explained in more detail below in connection to Figure 4.

Two or more MSDs can as mentioned above be aggregated in this manner and represented by a joint filter function, which is an advantage. An electrical energy storage system and an electric machine can for instance be combined and represented as a joint digital filter function that represents the combined capability of the two sub-systems. More than two sub-systems can also be combined in this manner, which is an advantage.

This way of describing the capability limitation of an MSD or system of MSDs allows for defining efficient interfaces between MSDs and MSD controllers, and also between vehicle motion management and systems and higher layer control systems, such as control systems for autonomous drive (AD) and the like.

The interface between, e.g., a VMM system and a TSM system for communicating MSD capability may be represented as a record such as the one below, where each MSD or MSD subsystem is associated with a respective row. There will be one row for each MSD, and possibly also rows for subsystems of MSDs.

With reference to Figures 3A-C, the digital filter function that provides information about the time-dependent capability limitation of a given MSD can be implemented at the request generator, i.e., at the device that generates the actuator request that is sent to the MSD to trigger some form of actuation, as illustrated in Figure 3A. In this case the request generator obtains the filter parameters directly from the MSD, but it can also obtain the filter parameters in some other way, such as from memory or from some other device, and then filters the MSD motion request signal sent to the MSD using the digital filter function defined by the filter parameters. This way the MSD will not receive an MSD request signal that breaches the capability limitation of the MSD. The request generator basically modulates the nominal MSD request signal using the digital filter function to obtain a capability limited MSD request signal that can be sent to the MSD device without risking over-actuation that results in, e.g., overheating, excessive wear, or significantly increased energy consumption.

With reference to Figure 3B, the MSD can of course also implement the digital filter function, in order to protect itself from nominal MSD request signals that breach the time-dependent capability limitation of the MSD. The MSD may then feed a capability limit signal back to the request generator informing it that the MSD has now reached its capability limit, for the time being at least, if the Nominal MSD request signal exceeds the capability limited MSD request signal obtained from filtering the nominal MSD request signal using the digital filter function.

Figure 3C illustrates an implementation where a separate request limiter device implements the digital filter function. This intermediate request policing function receives the nominal MSD requests from the request generator, filters the requests using the digital filter function, and then passes the capability limited MSD request signal to the MSD for actuation. The filter parameters may be sent to the intermediate policing function by the MSD, or by some other entity. The request limiter can be interleaved in the control chain for a given MSD in order to protect it from over-actuation in an efficient manner. The request limiter also functions as a diagnostic system that detects over-actuation, which is an advantage. To detect over-actuation the request limiter can monitor a difference between the nominal MSD request signal and the capability limited MSD request signal. The power of this difference signal can be used to detect over-actuation, e.g., by comparing it to a threshold. The energy of this difference signal is indicative of the amount of over-actuation over time.

Figure 12 shows an example of allowed temperature increase in a device. It is desired to utilize the device as much as possible, without damaging the device or causing hazard. As the temperature increases, the actuator can be utilized less, as a function of the increase in temperature. Figure 13 shows a digital filter function, characterized by a step response, associated with the temperature characteristics illustrated in Figure 12. The step response shows allowable MSD request signal amplitude vs time. The amplitude is here given in power units (p.u.), which is a general unit indicative of power. The typical specification of power limitation is illustrated as the “staircase” curve, and it is noted that the step response has a much larger area underneath it compared to this typical specification of power limitation, which means that the actuator can be used more efficiently if the capability limitation of the actuator is represented as the step response.

Figure 14 illustrates a Bode diagram corresponding to the step response, and also a simplified digital filter function of reduced order. This is an example of filter parameters.

Figure 4 shows nominal and capability limited MSD request signals according to an example. The nominal MSD request signal u is illustrated by the dashed line, and the capability limited MSD request signal Mii_m is shown by the solid line. An advantage of representing the timedependent capability limitation of the MSD in this way is that the small signal behavior of the MSD request signal is preserved even when the MSD is operating in limited state, as illustrated by Figure 4. In other words, by processing the nominal MSD request signal by the digital filter function that is indicative of the time-dependent capability limitation of the MSD, a capability limited MSD request signal is obtained that still comprises the small signal characteristics of the nominal MSD request signal. This allows a more refined control of the MSD, even when the MSD is operating in its capability limited mode.

Figure 5 schematically illustrates functionality 500 for controlling the vehicle 100 by some example MSDs here comprising brake actuators, propulsion actuators, and power steering, with respective controllers collectively referred to herein as MSD control 530. A TSM function 510 such as a human driver, an ADAS system, or an AD system, plans the driving operation of the vehicle 100 with a time horizon of 10 seconds or so. This time period corresponds to, e.g., the time it takes for the vehicle 100 to negotiate a curve or the like. The vehicle maneuvers, planned and executed by the TSM function 510, can be associated with acceleration profiles a_req and curvature profiles Cr_eq which describe a desired target vehicle velocity in the vehicle forward direction and turning to be maintained for a given maneuver. The TSM function continuously requests the desired acceleration profiles a_req and steering angles (or curvature profiles c_req) from the VMM system 520 which performs force allocation to meet the requests from the TSM function in a safe and robust manner. The force allocation is then translated into MSD request signals 575 that are sent to the different MSDs on the vehicle 100.

Each wheel 101, 102, 103 on the vehicle 100 has a longitudinal velocity component v_x and a lateral velocity component v_y (in the coordinate system of the wheel or in the coordinate system of the vehicle, depending on implementation). There is a longitudinal tyre force F_x and a lateral tyre force F_y, and also a normal force F_z acting on the wheel. The MSD request signals are generated at least in part to obtain a desired set of tyre forces from the different wheels on the tractor 110 and the trailer 120.

The VMM system 520 operates with a time horizon of about 1 second or so, and continuously transforms the acceleration profiles a_req and curvature profiles c_req from the TSM function 510 into MSD motion requests 531, 532, 533 for controlling vehicle motion functions, actuated by the different MSDs of the vehicle 100 which report back capabilities and status information 534, 535, 536 to the VMM function 520, which in turn may be used as constraints in the MSD coordination function 570. The different capabilities and status information 534, 535, 536 is represented at least in part by digital filter functions as discussed herein. The capability information is consolidated by the MSD capability function 580 that supports the MSD coordination function 570, e.g., by defining constraints to be used in the optimization of MSD request signals. In this example the MSDs send filter parameters {FILT 1}, {FILT 2},{FILT 3} to the MSD capability function 580, but the filter parameters can also be obtained from other sources, such as from memory or from an external source such as the server 160.

The VMM system 520 performs vehicle state or motion estimation 550, i.e., the VMM system 520 continuously determines a vehicle state s as function of time t comprising positions, speeds, accelerations, and articulation angles of the different units in the vehicle combination by monitoring operations using various sensors 540 arranged on the vehicle 100, often but not always in connection to the MSDs. The vehicle state at a future time instant can also be predicted by a state prediction function 555. This vehicle state prediction function may be realized by a vehicle model having a vehicle state which can be extrapolated into a predicted vehicle state, given a current vehicle state, and optionally also given the current vehicle motion request. The sensor systems 540 on the vehicle 100 may also be associated with capability limitations, sent to the state estimation function 550 as filter parameters. A sensor capability limitation may, e.g., be caused by limitations in the data connection between sensor and control unit, which can support a high data rate for a transient period of time, and a lower data rate for a longer period of time. This sensor capability limitation information can be used by the state estimation function to request data from the sensors in a way that does not overload the communication buses on the vehicle 100.

The result of the state estimation 550 and optionally also the state prediction 555, i.e., the estimated vehicle state s at one or more time instants, is input to a force generation module 560 which determines the required global forces V=[Vi, V2] for the different vehicle units to cause the vehicle 100 to move according to the requested acceleration and curvature profiles Hreq, Creq, and to behave according to the desired vehicle behavior. This example has two vehicle units. More vehicle units are possible, and also a single vehicle unit, e.g., in case the vehicle is a rigid truck or a passenger car. The required global force vector V is input to the MSD coordination function 570 which allocates tyre forces and coordinates other MSDs such as steering and suspension. The coordination by the MSD coordination function is advantageously performed by taking the MSD capabilities into account.

The MSD coordination function outputs an MSD control allocation for the i:th wheel, i.e., a capability limited MSD motion request signal, which may comprise any of a torque Ti, a longitudinal wheel slip Xi, a wheel rotational speed ®i, and/or a wheel steering angle 8i. The capability limited MSD request signal may also comprise a power to be delivered by a battery system. The coordinated MSDs then together provide the desired lateral Fy and longitudinal Fx forces on the vehicle units, as well as the required moments Mz, to obtain the desired motion by the vehicle combination 100. Thus, according to some aspects of the present disclosure, the VMM system 520 manages both force generation and MSD coordination, i.e., it determines what forces that are required at the vehicle units in order to fulfil the requests from the TSM function 510, for instance to accelerate the vehicle according to a requested acceleration profile requested by TSM and/or to generate a certain curvature motion by the vehicle also requested by TSM. The forces may comprise e.g., yaw moments Mz, longitudinal forces Fx and lateral forces Fy, as well as different types of torques to be applied at different wheels. The forces are determined such as to generate the vehicle behavior which is expected by the TSM function in response to the control inputs generated by the TSM function 510. To give an example of how an MSD coordination function 570 might operate, consider a control problem where x = [x_lt x_lt is a vector of MSD motion requests, v is a vector that represents a desired set of global vehicle forces to be generated, B is a control effectiveness matrix, and x_d is a vector of desired MSD motion requests. The vector of desired motion requests may, e.g., comprise a default actuator state associated with the smallest energy consumption or the like. The MSD coordination problem can then be cast as x* = arg

subject to x_t < x < x_u

Where W_x and W_v are weighting matrices, y is a tuning parameter, and x_t < x < x_u are constraints imposed on the MSD coordination optimization problem. The constraints x_t and x_u are determined based on the different filter parameters of the MSDs, e.g., as uum = h * u, maximum limit > u > continuous limit where h is the digital filter function of a given MSD.

In this way the MSD coordination function 570 is generally constrained in its allocation of motion requests to the different MSDs by MSD capabilities obtained from an MSD capability function such as the step response representations discussed herein. Each MSD has its limits when it comes to actuation. A propulsion device such as an electric machine is for instance associated with time-dependent limitations on the torque that can be delivered, as is a brake device. The steering system of a vehicle also has its limitations, such as the maximum achievable steering rate and steering angle.

Figure 6 schematically illustrates example functionality 600 for controlling an example wheel 101 on the vehicle 100 to generate a longitudinal wheel tyre F_x and a lateral wheel force F_y, by some example MSDs here comprising a friction brake 650 (such as a disc brake or a drum brake), a propulsion device 630 and a power steering arrangement 640. The friction brake 650 and the propulsion device 630 are examples of capability limited wheel torque generating devices, which can be controlled by one or more motion support device control units 530. The control is based on measurement data obtained from, e.g., a wheel speed sensor (WS) 610 in combination with data from one or more inertial measurement units (IMU) 620 and optionally also based on data from other vehicle state sensors 540, such as radar sensors, lidar sensors, and also vision based sensors such as camera sensors and infra-red detectors. In this case the MSD control subsystem 530 sends filter parameters indicative of the different MSD capability limitations in the system to the VMM system 520. MSD requests are continuously generated by the VMM function 520 which comprises the MSD capability function 580 that is parameterized based on the filter parameters of the different MSDs on the vehicle. In this way over-actuation of one or more MSD devices is prevented in an efficient manner.

To summarize, there is disclosed herein a computer-implemented control system 300, 310, 320, 500, 600 for controlling at least one MSD 530, 540, 550 on a heavy-duty vehicle 100. The computer-implemented control system comprises centralized or distributed processing circuitry arranged to obtain a set of filter parameters that define a digital filter function associated with a time-dependent capability of the MSD 530, 540, 550, i.e., an actuator capability of the MSD as function of time. The digital filter function has a step response that is indicative of the MSD capability limitation, as was discussed above in connection to Figure 2. In some case the digital filter function has a step response that describes decreasing MSD actuator capability as function of time, in response to a step function nominal MSD request signal. However, some MSDs are also associated with an increased capability as a function of time. For instance, some MSDs such as turbo fans and the like only attain full performance after some time period. This type of time dependency can also be represented using the type of digital filter approach described herein. The set of filter parameters may comprise a set of impulse response parameters, a reference capability level and a sampling time duration. The set of filter parameters may be given relative to a continuous limit level of the MSD, or relative to some other reference actuator level. The time-dependent capability of an MSD is often known from its specification. If the time-dependent capability of an MSD is not known, it can be determined from computer simulation and/or from laboratory tests in a straight forward manner.

The processing circuitry is arranged to obtain a nominal MSD request signal indicative of a desired actuation by the MSD. This nominal MSD request can be generated in many different ways, either explicitly as a desired actuation, or implicitly by formulating a control allocation problem and solving the control allocation problem as was discussed above in connection to Figure 5. The processing circuitry processes the nominal MSD request signal by the digital filter function into a capability limited MSD request signal, and controls the at least one MSD based on the capability limited MSD request signal. This way over-actuation of one or more MSDs is avoided in an efficient manner. The processing circuitry can advantageously be arranged to process the nominal MSD request signal by filtering the nominal MSD request signal by the digital filter function to obtain the capability limited MSD request signal.

The set of filter parameters can be obtained at least in part directly from the MSD 530, 540, 550, from an external source such as the remote server 160, or from memory as a pre-stored set of filter parameters. The processing circuitry may also be arranged to obtain the set of filter parameters as a function of at least one other parameter, such as operating temperature, wear state, energy consumption, or some other state variable of the MSD. Figures 7A and 7B show example capability limitation functions that change with temperature. The nominal capability function is shown as a solid line and the adjusted capability function after an increase in device temperature is shown as a dashed line.

The MSD may be an electric machine as discussed above, and the at least one other parameter may comprise a state of charge, SoC, of a battery system associated with the electric machine.

Figure 8 shows an example where a battery is used to power an electric motor drive system that in turn provides torque to a wheel. Each MSD has its respective digital filter capability function, which in this case also depends on the temperature of the device. The two digital filter functions is then combined by taking the minimum of the two over time to obtain a combined MSD capability function that describes the time dependence of capability of the joint system. Thus, according to some aspects, the processing circuitry is arranged to process two or more capability limited MSD request signals into an aggregated capability limited MSD request signal. The aggregated capability may be obtained by taking the smallest capability of the MSD components in the subsystem at each time instant.

The processing circuitry can also be arranged to determine a difference signal as the difference between nominal MSD request signal and the capability limited MSD request signal, and to trigger an action in case the difference satisfies a pre-determined magnitude criterion. This way the MSD request signal can be monitored to see if too high requests are being sent.

The processing circuitry may also be arranged to execute an MSD control allocation routine or MSD coordination function 570 involving a plurality of MSDs, where a set of constraints associated with the control allocation routine are defined based on the set of filter parameters. The MSD control allocation routine can be configured to solve a constrained optimization problem, where the constraints are determined based on the set of filter parameters. The MSD control allocation routine may also be configured to solve an optimization problem associated with one or more cost functions, where the cost functions are configured in dependence of any of; an energy expenditure of MSD actuators, a wear incurred on MSD actuators, and a passenger convenience metric.

FIG. 9 is a schematic diagram of a computer system 900 for implementing examples disclosed herein. The computer system 900 is adapted to execute instructions from a computer-readable medium to perform these and/or any of the functions or processing described herein. The computer system 900 may be connected (e.g., networked) to other machines in a LAN, an intranet, an extranet, or the Internet. While only a single device is illustrated, the computer system 900 may include any collection of devices that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein. Accordingly, any reference in the disclosure and/or claims to a computer system, computing system, computer device, computing device, control system, control unit, electronic control unit (ECU), processor device, processing circuitry, etc., includes reference to one or more such devices to individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein. For example, a control system may include a single control unit, or a plurality of control units connected or otherwise communicatively coupled to each other, such that any performed function may be distributed between the control units as desired. Further, such devices may communicate with each other or other devices by various system architectures, such as directly or via a Controller Area Network (CAN) bus, etc.

The computer system 900 may comprise at least one computing device or electronic device capable of including firmware, hardware, and/or executing software instructions to implement the functionality described herein. The computer system 900 may include processing circuitry 902 (e.g., processing circuitry including one or more processor devices or control units), a memory 904, and a system bus 906. The computer system 900 may include at least one computing device having the processing circuitry 902. The system bus 906 provides an interface for system components including, but not limited to, the memory 904 and the processing circuitry 902. The processing circuitry 902 may include any number of hardware components for conducting data or signal processing or for executing computer code stored in memory 904. The processing circuitry 902 may, for example, include a general-purpose processor, an application specific processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a circuit containing processing components, a group of distributed processing components, a group of distributed computers configured for processing, or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. The processing circuitry 902 may further include computer executable code that controls operation of the programmable device.

The system bus 906 may be any of several types of bus structures that may further interconnect to a memory bus (with or without a memory controller), a peripheral bus, and/or a local bus using any of a variety of bus architectures. The memory 904 may be one or more devices for storing data and/or computer code for completing or facilitating methods described herein. The memory 904 may include database components, object code components, script components, or other types of information structure for supporting the various activities herein. Any distributed or local memory device may be utilized with the systems and methods of this description. The memory 904 may be communicably connected to the processing circuitry 902 (e.g., via a circuit or any other wired, wireless, or network connection) and may include computer code for executing one or more processes described herein. The memory 904 may include non-volatile memory 908 (e.g., read-only memory (ROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), etc.), and volatile memory 910 (e.g., random-access memory (RAM)), or any other medium which can be used to carry or store desired program code in the form of machineexecutable instructions or data structures, and which can be accessed by a computer or other machine with processing circuitry 902. A basic input/output system (BIOS) 912 may be stored in the non-volatile memory 908 and can include the basic routines that help to transfer information between elements within the computer system 900.

The computer system 900 may further include or be coupled to a non-transitory computer- readable storage medium such as the storage device 914, which may comprise, for example, an internal or external hard disk drive (HDD) (e.g., enhanced integrated drive electronics (EIDE) or serial advanced technology attachment (SATA)), HDD (e.g., EIDE or SATA) for storage, flash memory, or the like. The storage device 914 and other drives associated with computer- readable media and computer-usable media may provide non-volatile storage of data, data structures, computer-executable instructions, and the like.

Computer-code which is hard or soft coded may be provided in the form of one or more modules. The module(s) can be implemented as software and/or hard-coded in circuitry to implement the functionality described herein in whole or in part. The modules may be stored in the storage device 914 and/or in the volatile memory 910, which may include an operating system 916 and/or one or more program modules 918. All or a portion of the examples disclosed herein may be implemented as a computer program 920 stored on a transitory or non- transitory computer-usable or computer-readable storage medium (e.g., single medium or multiple media), such as the storage device 914, which includes complex programming instructions (e.g., complex computer-readable program code) to cause the processing circuitry 902 to carry out actions described herein. Thus, the computer-readable program code of the computer program 920 can comprise software instructions for implementing the functionality of the examples described herein when executed by the processing circuitry 902. In some examples, the storage device 914 may be a computer program product (e.g., readable storage medium) storing the computer program 920 thereon, where at least a portion of a computer program 920 may be loadable (e.g., into a processor) for implementing the functionality of the examples described herein when executed by the processing circuitry 902. The processing circuitry 902 may serve as a controller or control system for the computer system 900 that is to implement the functionality described herein.

The computer system 900 may include an input device interface 922 configured to receive input and selections to be communicated to the computer system 900 when executing instructions, such as from a keyboard, mouse, touch-sensitive surface, etc. Such input devices may be connected to the processing circuitry 902 through the input device interface 922 coupled to the system bus 906 but can be connected through other interfaces, such as a parallel port, an Institute of Electrical and Electronic Engineers (IEEE) 1394 serial port, a Universal Serial Bus (USB) port, an IR interface, and the like. The computer system 900 may include an output device interface 924 configured to forward output, such as to a display, a video display unit (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)). The computer system 900 may include a communications interface 926 suitable for communicating with a network as appropriate or desired. The operational actions described in any of the exemplary aspects herein are described to provide examples and discussion. The actions may be performed by hardware components, may be embodied in machine-executable instructions to cause a processor to perform the actions, or may be performed by a combination of hardware and software. Although a specific order of method actions may be shown or described, the order of the actions may differ. In addition, two or more actions may be performed concurrently or with partial concurrence.

Figure 10 is a flow chart illustrating methods that correspond to the different technical features of the computer system and the vehicles discussed herein. The flow chart illustrates a computer- implemented method for controlling at least one MSD 530, 540, 550 on a heavy-duty vehicle 100. The method comprises obtaining SI, by processing circuitry of the control system, a set of filter parameters that define a digital filter function associated with a capability of the MSD 530, 540, 550 as function of time, obtaining S2, by processing circuitry of the control system, a nominal MSD request signal indicative of a desired actuation by the MSD, processing S3, by processing circuitry of the control system, the nominal MSD request signal by the digital filter function into a capability limited MSD request signal, and controlling S4, by processing circuitry of the control system, the at least one MSD based on the capability limited MSD request signal.

The various technical features of the processing circuitry discussed above can be incorporated into the disclosed method as optional method parts.

Figure 11 illustrates a computer readable medium 1110 carrying a computer program comprising program code means 1120 for performing the methods illustrated in Figure 10 and the techniques discussed herein, when said program product is run on a computer. The computer readable medium and the code means may together form a computer program product 1100.

The operational steps described in any of the exemplary aspects herein are described to provide examples and discussion. The steps may be performed by hardware components, may be embodied in machine-executable instructions to cause a processor to perform the steps, or may be performed by a combination of hardware and software. Although a specific order of method steps may be shown or described, the order of the steps may differ. In addition, two or more steps may be performed concurrently or with partial concurrence. The terminology used herein is for the purpose of describing particular aspects only and is not intended to be limiting of the disclosure. As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items. It will be further understood that the terms "comprises," "comprising," "includes," and/or "including" when used herein specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It will be understood that, although the terms first, second, etc., may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element without departing from the scope of the present disclosure.

Relative terms such as "below" or "above" or "upper" or "lower" or "horizontal" or "vertical" may be used herein to describe a relationship of one element to another element as illustrated in the Figures. It will be understood that these terms and those discussed above are intended to encompass different orientations of the device in addition to the orientation depicted in the Figures. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element, or intervening elements may be present. In contrast, when an element is referred to as being "directly connected" or "directly coupled" to another element, there are no intervening elements present.

Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. It will be further understood that terms used herein should be interpreted as having a meaning consistent with their meaning in the context of this specification and the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein. It is to be understood that the present disclosure is not limited to the aspects described above and illustrated in the drawings; rather, the skilled person will recognize that many changes and modifications may be made within the scope of the present disclosure and appended claims. In the drawings and specification, there have been disclosed aspects for purposes of illustration only and not for purposes of limitation, the scope of the inventive concepts being set forth in the following claims.

Claims

1. A computer-implemented control system (300, 310, 320, 500, 600) for controlling at least one motion support device, MSD, (530, 540, 550) on a heavy-duty vehicle (100), the computer-implemented control system comprising processing circuitry arranged to obtain a set of filter parameters that define a digital filter function associated with a capability of the MSD (530, 540, 550) as function of time, obtain a nominal MSD request signal indicative of a desired actuation by the MSD, process the nominal MSD request signal by the digital filter function into a capability limited MSD request signal, and control the at least one MSD based on the capability limited MSD request signal.

2. The computer-implemented control system (300, 310, 320, 500, 600) according to claim 1, where the processing circuitry is arranged to obtain the set of filter parameters at least in part from the MSD (530, 540, 550).

3. The computer-implemented control system (300, 310, 320, 500, 600) according to claim 1 or 2, where the processing circuitry is arranged to obtain the set of filter parameters at least in part as a pre-stored set of filter parameters.

4. The computer-implemented control system (300, 310, 320, 500, 600) according to any previous claim, where the processing circuitry is arranged to obtain the set of filter parameters as a function of at least one other parameter.

5. The computer-implemented control system (300, 310, 320, 500, 600) according to claim 4, where the at least one other parameter comprises an operating temperature of the MSD.

6. The computer-implemented control system (300, 310, 320, 500, 600) according to claim 4 or 5, where the at least one other parameter comprises a wear state of the MSD.

7. The computer-implemented control system (300, 310, 320, 500, 600) according to any of claims 4-6, where the MSD is an electric machine and the at least one other parameter comprises a state of charge, SoC, of a battery system associated with the electric machine.

8. The computer-implemented control system (300, 310, 320, 500, 600) according to any previous claim, where the digital filter function is a step response describing decreasing MSD capability as function of time, in response to a step function nominal MSD request signal.

9. The computer-implemented control system (300, 310, 320, 500, 600) according to any previous claim, where the set of filter parameters comprise a set of impulse response parameters, a reference capability level and a sampling time duration.

10. The computer-implemented control system (300, 310, 320, 500, 600) according to any previous claim, where the set of filter parameters are given relative to a continuous limit level of the MSD.

11. The computer-implemented control system (300, 310, 320, 500, 600) according to any previous claim, where the processing circuitry is arranged to process the nominal MSD request signal by filtering the nominal MSD request signal by the digital filter function to obtain the capability limited MSD request signal.

12. The computer-implemented control system (300, 310, 320, 500, 600) according to any previous claim, where the processing circuitry is arranged to determine a difference signal as the difference between nominal MSD request signal and the capability limited MSD request signal, and to trigger an action in case the difference satisfies a pre-determined magnitude criterion.

13. The computer-implemented control system (300, 310, 320, 500, 600) according to claim 12, where a power of the difference signal is compared to pre-determined detection criteria to detect over-actuation of an MSD.

14. The computer-implemented control system (300, 310, 320, 500, 600) according to claim 12 or 13, where an energy of the difference signal is compared to pre-determined detection criteria to detect over-actuation of an MSD.

15. The computer-implemented control system (300, 310, 320, 500, 600) according to any previous claim, where the processing circuitry is arranged to process two or more capability limited MSD request signals into an aggregated capability limited MSD request signal.

16. The computer-implemented control system (300, 310, 320, 500, 600) according to any previous claim, where the processing circuitry is arranged to execute an MSD control allocation routine or MSD coordination function (570) involving a plurality of MSDs, where a set of constraints associated with the control allocation routine are defined based on the set of filter parameters.

17. The computer-implemented control system (300, 310, 320, 500, 600) according to claim 16, where the MSD control allocation routine or MSD coordination function (570) is configured to solve a constrained optimization problem, where the constraints are determined based on the set of filter parameters.

18. The computer-implemented control system (300, 310, 320, 500, 600) according to claim 16 or 17, where the MSD control allocation routine or MSD coordination function (570) is configured to solve an optimization problem associated with one or more cost functions, where the cost functions are configured in dependence of any of; an energy expenditure of MSD actuators, a wear incurred on MSD actuators, and a passenger convenience metric.

19. The computer-implemented control system (300, 310, 320, 500, 600) according to any previous claim, arranged to transmit motion requests to a plurality of MSDs comprising at least one propulsion device (530), at least one power steering system (540), and at least one at least one friction brake (550).

20. A computer-implemented method for controlling at least one motion support device, MSD, (530, 540, 550) on a heavy-duty vehicle (100), the method comprising obtaining (SI), by processing circuitry of the control system, a set of filter parameters that define a digital filter function associated with a capability of the MSD (530, 540, 550) as function of time, obtaining (S2), by processing circuitry of the control system, a nominal MSD request signal indicative of a desired actuation by the MSD, processing (S3), by processing circuitry of the control system, the nominal MSD request signal by the digital filter function into a capability limited MSD request signal, and controlling (S4), by processing circuitry of the control system, the at least one MSD based on the capability limited MSD request signal.

21. A computer program product comprising program code for performing, when executed by the processing circuitry, the method of claim 20.

22. A non-transitory computer-readable storage medium comprising instructions, which when executed by processing circuitry, cause the processing circuitry to perform the method of claim 20.