CN116026609A - A method for estimating actual driving resistance of vehicles - Google Patents

Abstract

The invention relates to a method for estimating the actual running resistance of a vehicle, which is characterized by comprising the following steps: the vehicle is driven normally based on an actual road, and the vehicle speed, the engine rotation speed, the torque, the friction torque, the accelerator opening, the gear and the oil injection signal information are collected through a vehicle bus, an external instrument or a built-in sensor of the vehicle when the vehicle runs; the method comprises the steps of acquiring information of vehicle speed, acceleration, gradient and direction angle by adopting a GPS, a gyroscope and an accelerometer or utilizing a vehicle built-in inertial navigation system, estimating an actual road resistance curve coefficient value based on the information, and further combining gradient resistance and acceleration resistance calculation to estimate the actual road resistance. The beneficial effects are that: the method is suitable for the requirements of measuring and calculating the actual road resistance of the vehicle in all real scenes, and improves the testing efficiency; the obtained result represents the actual road resistance of the current condition, and can better meet the test requirement; based on the prior art of vehicles, the estimation and prediction of the road running resistance can be realized.

Description

A method for estimating actual driving resistance of vehicles

technical field

The invention belongs to the technical field of vehicle detection, in particular to a method for estimating the actual running resistance of a vehicle.

Background technique

The test and evaluation of vehicle dynamics, fuel consumption, and emissions based on the chassis dynamometer is a commonly used test method in the design and development of modern automobile products and performance evaluation tests. By controlling the test conditions, the actual driving resistance of the car can be accurately simulated on the chassis dynamometer and the test can be carried out on this basis. When performing the chassis dynamometer test, before simulating the road driving resistance, the road resistance curve of the car must be determined first. Set the parameters of the chassis dynamometer, because the empirical values recommended by laws and regulations are generally different from the actual values, so the test method is often used to obtain the relationship curve between the actual resistance of the vehicle and the speed of the vehicle. That is, the vehicle resistance value can be obtained by looking up the table according to the sliding resistance curve through the vehicle speed.

At present, the standard method of vehicle driving resistance detection mostly adopts the sliding method (such as the relevant provisions in GB18352-2016, GB/T27840-2021 and other standards). The wind speed that interferes with the test results), after the car accelerates to the specified speed on the special straight road test track, put the transmission in the "neutral" position and coast to a low speed or even 0 speed, and use the data acquisition system with GPS positioning to record the whole taxi synchronously Data, obtain the quadratic functional relationship between the resistance of the vehicle during the sliding process and the speed of the vehicle through a standard calculation method, that is, the relationship of F=A+B V+C V ² , where F is the sliding resistance, and V is the speed of the vehicle , A, B, C are drag coefficients respectively.

This method can obtain a relatively accurate vehicle resistance curve, which is suitable for standard testing of laboratory regulations and standards, but there are certain limitations. First of all, since it is a specific test vehicle with a fixed load, the sliding test is completed under a specific test site and a specific temperature condition, the sliding resistance curve cannot represent the sliding resistance under other conditions. Because changes in road properties, altitude, load, temperature, and vehicle conditions in actual conditions will all correspond to a specific resistance curve, if you want to use the test methods required by the above regulations and standards to obtain sliding resistance curves for all other conditions, it is not right. Realistically, approximate values can only be obtained through some empirical parameter corrections, such as temperature correction and altitude correction for the sliding resistance curve, but there will be problems with large errors in the correction values or cannot be corrected. Therefore, there are currently deficiencies in technology and methods for some development and test requirements that want to obtain actual road sliding resistance curves.

With the development of vehicle technology, the vehicle energy-saving control technology based on model prediction needs to realize the intelligent control of the power system according to the actual resistance characteristics. If the sliding resistance curve of the actual road can be obtained, it is also a solution for real-time vehicle traction prediction.

Contents of the invention

The purpose of the present invention is to overcome the deficiencies of the above-mentioned technologies, and provide a method for estimating the actual driving resistance of a vehicle, which can be used not only for estimating and identifying the actual road resistance curve, but also for predicting the traction force of the vehicle's actual road running required by the vehicle model control strategy.

In order to achieve the above object, the present invention adopts the following technical solutions: a method for estimating the actual running resistance of a vehicle. Its characteristics are: the vehicle is normally driven on the actual road, and the vehicle speed, engine speed, torque, friction torque, accelerator opening, gear position and fuel injection signal and other information are collected through the vehicle bus, external instruments or built-in sensors of the vehicle; Using GPS, gyroscope and accelerometer, or using the vehicle's built-in inertial navigation system to collect vehicle speed, acceleration, slope, and direction angle information, based on these data, estimate the actual road resistance curve coefficient value, and further, combined with slope resistance and acceleration resistance calculation, The actual road resistance can be estimated, the specific steps are as follows:

Step 1, judging traffic conditions, weather conditions and road conditions, so as to meet the vehicle operating environment conditions when carrying out data collection described in the present invention;

Step 2. Judging the vehicle warm-up state: select a medium-high speed running vehicle so that the vehicle meets the preheating requirements, and the vehicle coolant temperature and engine oil temperature reach a stable state;

Step 3, driving requirements: choose a relatively straight actual road, drive the vehicle with a relatively stable driving behavior, try to avoid driving behaviors such as rapid acceleration, deceleration and quick adjustment of the steering wheel (such as frequent lane changes and steering), and record the required driving behavior in real time. Vehicle operation data. The corresponding data of sudden acceleration and deceleration, braking, gear shifting, and steering behaviors need to be eliminated and not used in subsequent calculations;

Step four, data collection. In the process of driving the vehicle, collect the relevant data when the vehicle is running at a collection frequency not lower than 1Hz, and collect the vehicle speed V, engine speed n, engine torque T _tq , engine friction torque T _m , accelerator opening through the CAN bus of the vehicle OBD port speed, gear, fuel injection signal information; adopt GPS, gyroscope and accelerometer to collect vehicle speed, acceleration a, slope θ or i, direction angle information; select "constant speed driving method" or "actual driving speed segment Extraction method" to complete the data collection;

Step five, parameter estimation. According to the test data obtained in step 4, data screening, processing and calculation are carried out to obtain the estimated value of the drag curve coefficient of the vehicle's actual road.

Further, judging the traffic conditions, weather conditions and road conditions as described in step one is: under the condition of no rain, snow and fog, the relative humidity of temperature -20～40°C, humidity＜95%, and the relative humidity below 5000m above sea level are both Applicable; road traffic index ≤ 2; wind speed ≤ level 2, average ground wind speed ≤ 3m/s, gust not greater than 5m/s.

Further, the actual operation data collection and calculation of the vehicle described in step four. Let F _t represent the driving force of the vehicle, T _tq represent the engine torque, i _g represent the transmission ratio of the transmission, i ₀ represent the transmission ratio of the final drive, η represent the mechanical efficiency of the drive train, and r represent the wheel radius, then the driving force F _t is :

If the vehicle is coasting with gears, the engine stops fuel injection, and is in the reverse drag state, the engine torque T _tq is a negative value, which is set to T _m , then the driving force F _t is:

Among them, the engine torque T _tq and reverse drag torque T _m are obtained and recorded in real time from the vehicle CAN bus information, the transmission ratio i _g and the final drive ratio i ₀ are obtained through the vehicle CAN bus information; the wheel radius r is the static radius of the wheel value.

The relationship between engine speed and vehicle speed is:

Among them, V is the driving speed of the vehicle, which is obtained in real time from GPS information or CAN bus information; n is the engine speed, which is obtained in real time from CAN bus information, and the relationship between the driving force F _t of the vehicle and the engine speed, torque, and vehicle speed is:

If the vehicle is slipping backwards with a gear, the formula is:

When a car is running at a constant speed on a level road, it needs to overcome the rolling resistance from the ground and the air resistance from the air. Let the rolling resistance be F _f and the air resistance be F _w . _i , the acceleration resistance F _j that needs to be overcome when the vehicle accelerates, and the driving force Ft of the vehicle is the sum of all resistances, namely:

F _t =F _f +F _w +F _i +F _j

Among them, "F _f + F _w " is the quadratic function of the vehicle's driving speed, that is, the resistance determined by the values of A, B, and C in the quadratic function A+B·V+C·V ² " of the standard sliding method value;

The slope resistance F _i is the component force generated by the gravity of the vehicle along the slope when the vehicle is driving on the slope. Under normal circumstances, the slope of the general road is small. The maximum longitudinal slope in the area is 3%, and the slope in the mountainous and hilly area of the fourth-class road is 9%. The road slope is expressed by the ratio of the slope height h (unit m) to the bottom length s (unit m), that is:

Therefore, if the slope of the road is small, sinθ≈tanθ=i, then:

F _i =M·g·sinθ

Among them, M is the mass of the vehicle (unit kg), g is the acceleration of gravity (9.8m/s ² ); θ is the longitudinal slope angle of the road; if the road is basically straight, the value of F _i is approximately 0.

Acceleration resistance F _j is the inertial force when the vehicle accelerates and overcomes its mass acceleration. The mass of the car is divided into translational mass and rotational mass. When the car accelerates, the translational mass accelerates to generate inertial force, and the rotational mass generates inertial moment.

为车辆的行驶加速度a(单位m/s²)，由以上公式推导可得：Among them, m _r is the rotating mass, which refers to the equivalent effective mass (unit: kg) of all rotating parts and wheels on the vehicle when the vehicle is driving in neutral on the road, and m _r can be estimated based on 3% of the reference mass of the vehicle ,

is the driving acceleration a of the vehicle (unit m/s ² ), deduced from the above formula:

F _t ＝(A+B·V+C·V ² )+M·g·sinθ+(M+m _r )·a, combined with the above calculation formula of F _t , we can further get:

Right now:

Or, when coasting with gear:

Further, the constant-speed driving method described in step 4 is preferably selected as the method for determining the vehicle resistance coefficients A, B, and C under relatively straight road conditions and good traffic conditions. At this time, the slope resistance Fi and the acceleration resistance F _j can be approximately zero. Select the highest test speed based on the actual road speed limit and the maximum speed limit of the vehicle. From high speed to low speed, change the speed no more than 20km/h, and gradually reduce the speed until the speed is lower than 20km/h. In order to ensure the effective fitting of the resistance curve, At least 5 speed point test data are guaranteed. At each speed point, keep the speed stable for a period of time to obtain enough data. Filter the calculation data, select the phase data of the driving behavior that the vehicle speed is basically stable, and the driver does not perform sudden acceleration and deceleration, braking, shifting, and large adjustment of the steering wheel as the calculation data. According to the formula (1), the second-by-second relationship between the driving resistance and the vehicle speed V is obtained. Quadratic function relation. According to the least squares regression method, the analysis obtained A, B, C values.

Further, the actual driving speed segment extraction method described in step 4: In a section of the test target road section, the vehicle is normally driven according to the actual traffic conditions, and the driving speed covers all normal speed ranges lower than the vehicle speed limit as far as possible, and avoids rapid acceleration, sudden Slow down and sharply adjust the driving behavior of the steering wheel. Judging the actual calculation data selection and the selected calculation formula according to the collected data. Select the data with relatively stable operation, no significant adjustments to the steering wheel, brakes, and gear shifts, and exclude data with a vehicle speed lower than 15km/h. If there is a sliding state in gear, select formula (2), otherwise select formula (1), and obtain the second-by-second quadratic functional relationship between driving resistance and vehicle speed V. According to the least squares regression method, the analysis obtained A, B, C values.

After determining the values of A, B, and C, if the vehicle has a built-in vehicle inertial navigation system, in the actual control of the vehicle, the slope information of the driving road can be obtained in real time, and further, the road geographic information can also be obtained through the Internet of Vehicles. The slope value of the route ahead can be known in advance, and the actual road resistance can be estimated according to the formula (1), thereby predicting the power demand and providing a solution for the predictive control of the vehicle.

Beneficial effects: compared with the prior art, the present invention 1) is suitable for all real scenes that need to measure the actual road resistance of the vehicle, and can be carried out anytime and anywhere without having to select a dedicated test site, which saves test costs and improves test efficiency ; 2) The method is flexible and simple, and can be repeated many times as needed, and the obtained results represent the actual road resistance of the current conditions, rather than empirical correction values, which can better meet the test requirements; 3) Based on existing vehicle technology , under the condition of not increasing the hardware cost, the method of the present invention can realize the estimation and prediction of the road running resistance in the model-based control strategy of the vehicle, and meet the technical requirements of the vehicle traction force predictive control.

Description of drawings

Fig. 1 overall flow chart of the method of the present invention.

FIG. 2 is an implementation flow chart of method 1 for estimating vehicle running resistance.

FIG. 3 is an implementation flow chart of method 2 for estimating vehicle running resistance.

Fig. 4 is a vehicle speed distribution diagram of test sampling points of a specific embodiment.

Fig. 5(a) is the corresponding data map of actual driving resistance and vehicle speed.

Fig. 5(b) is the fitting result of the running resistance curve of the specific embodiment.

Detailed ways

The specific implementation of the present invention will be described in detail below in conjunction with preferred embodiments.

See the accompanying drawings for details. This embodiment provides a method for estimating the actual driving resistance of a vehicle. The vehicle is normally driven on the actual road, and the vehicle speed, engine speed, torque, Information such as friction torque, accelerator opening, gear position and fuel injection signal; use GPS, gyroscope and accelerometer, or use the vehicle's built-in inertial navigation system to collect information on vehicle speed, acceleration, slope and direction angle, and based on these data, estimate the actual The coefficient value of the road resistance curve can be further combined with the calculation of slope resistance and acceleration resistance to estimate the actual road resistance. The specific steps are as follows:

Step 1, judging traffic conditions, weather conditions and road conditions.

Because it is testing the actual road resistance curve, extreme weather conditions and congested traffic conditions cannot be carried out. The inventive method needs to carry out under the condition of good weather conditions (no rain and snow, no fog), for general temperature and humidity conditions (as: -20～40 ℃, <95% relative humidity) and altitude range (below 5000m) ) are applicable. The road traffic should be smooth, and the traffic index should not exceed 2. In order to reduce the influence of wind speed on the resistance calculation, the wind speed should be as small as possible, and it is recommended to choose a wind condition not higher than level 2 (breeze). Generally, the average ground wind speed is required to be not higher than 3m/s, and the gust is not higher than 5m/s . If the traffic is smooth and the road is straight, basic constant speed driving can be guaranteed, and the "constant speed method" is preferred.

Step 2, judging the preheating state of the vehicle. The vehicle coolant temperature and engine oil temperature have reached a stable state. If the preheating state is not good, you can choose to run the vehicle at a medium and high speed to make the vehicle meet the preheating requirements.

Step 3: Driving requirements. Select method 1 or method 2 below to complete data collection. In general, choose a relatively straight actual road, drive the vehicle with a relatively stable driving behavior, try to avoid driving behaviors such as rapid acceleration, deceleration and quick adjustment of the steering wheel (such as frequent lane changes and steering), and record the required vehicle operating data in real time , the corresponding data of sudden acceleration and deceleration, braking, shifting, and large adjustment of the steering wheel need to be eliminated in subsequent calculations and will not be used.

Method 1: Constant speed driving method. Because this method is relatively simple to calculate, if there are relatively straight road conditions and traffic conditions are ideal, this method is preferred as the method for determining vehicle drag coefficients A, B, and C. Select the highest test vehicle speed based on the actual speed limit of the road and the maximum speed limit of the vehicle, from high speed to low speed (or low to high), and gradually change the vehicle speed at a speed not higher than 20km/h until the vehicle speed is lower than 20km/h. For each speed point, keep the speed stable for a period of time to ensure sufficient data. If you do not have the conditions for continuously variable speed driving, you can select the speed according to the actual conditions, and gradually complete the required data at different speed points.

Method 2: Actual driving speed segment extraction method. If the road and traffic conditions in method 1 are not available, the required data can be obtained by driving the vehicle normally according to the actual traffic conditions. In a section of the test target road section, the vehicle is driven normally according to the actual traffic conditions, and the driving speed covers all normal speed ranges below the vehicle speed limit as much as possible. For example, if the maximum speed limit of the vehicle is 100, then the vehicle can be changed at a speed not greater than 20km/h , adjust the speed of the vehicle according to the actual traffic conditions. It is not required to maintain a stable driving state during the driving process, and it is not required to increase or decrease the speed change. It can be driven at any speed according to actual needs, but it is required that the speed change should cover as much as possible. In the speed range of 100km/h, you can drive back and forth on this target road section, and try to avoid driving behaviors such as rapid acceleration, rapid deceleration and large adjustment of the steering wheel. After collecting enough vehicle speed coverage data, the data collection can be stopped, and the actual calculation data selection can be judged according to the collected data, and the selected calculation formula can be determined. Eliminate the vehicle data when driving behaviors such as rapid acceleration, deceleration, braking, shifting, and steering, as well as data with a vehicle speed lower than 15km/h, and other obviously abnormal data, intercept the actual operating data covering each speed point, and pass the accelerator pedal , gear and fuel injection signals, and judge the driving behavior in the state of sliding in gear.

Step four, data collection. During the process of driving the vehicle, collect relevant data while the vehicle is driving at a collection frequency not lower than 1Hz. Collect vehicle speed (V), engine speed (n), engine torque (T _tq ), engine friction torque (T _m ), throttle opening, gear position, fuel injection signal and other information through the CAN bus of the vehicle OBD port; use GPS , Gyroscope and accelerometer to collect vehicle speed, acceleration (a), slope (θ or i), and direction angle information. If the vehicle has a built-in inertial navigation system, the vehicle CAN bus can also obtain information such as slope, acceleration, and steering angle. The acceleration a can be obtained directly by the accelerometer, or can be calculated from the vehicle speed V. The mechanical efficiency η of the drive train can be a parameter value provided by the vehicle manufacturer, or a theoretically recommended value can be adopted. The vehicle mass M can be weighed or calculated from the loaded load.

Step five, parameter estimation. According to the test data obtained in step 4, filter the data, perform data processing and calculation, and obtain the estimated value of the drag curve coefficient of the vehicle's actual road. If method 1 is adopted, according to formula (1), the point-by-point quadratic function relationship between driving resistance and vehicle speed V is obtained at different vehicle speed stages. According to the least squares regression method, the analysis obtained A, B, C values. If method 2 is used, if the vehicle is in gear and coasting, select formula (2), otherwise select formula (1), and obtain the point-by-point quadratic function relationship between driving resistance and different vehicle speeds V. According to the least squares regression method, the analysis obtained A, B, C values.

After determining the values of A, B, and C, if the vehicle has a built-in vehicle inertial navigation system, in the actual control of the vehicle, the slope information of the driving road can be obtained in real time, and further, the road geographic information can also be obtained through the Internet of Vehicles. The slope value of the route ahead can be known in advance, and the actual road resistance can be estimated according to the resistance calculation formula, thereby predicting the power demand and providing a solution for the predictive control of the vehicle.

The resistance curve estimation algorithm is further described below in conjunction with a specific embodiment, taking the constant speed driving method as an example:

1) The maximum speed of the test vehicle is limited to 100km/h, with a speed change of 20km/h, select 20, 40, 60, 80, 100km/h as the speed selection point, and keep basically stable for more than 60s at each speed point, Finally, the data is used to eliminate the vehicle data of acceleration, deceleration, braking, shifting, and steering driving behaviors, as well as other obviously abnormal data, and only intercept the data of relatively stable operation at each speed point. The final data points obtained are shown in Figure 4 , each speed point data is about 400s. In the actual test process, the speed can be changed from low to high or from high to low. If the traffic conditions are limited, it can also be carried out in sections according to the actual situation, or the vehicle can be driven at random speed points to complete the required data of each speed point.

2) Since the road is basically straight and the vehicle speed is basically stable, the slope resistance Fi and acceleration resistance F _j are approximately 0, which can be ignored for calculation. The mechanical efficiency η of the transmission system adopts the recommended value of 0.84 based on theoretical experience. According to the formula (1), the second-by-second corresponding data of the actual driving resistance F _t and the vehicle speed V are finally calculated, as shown in Figure 5(a). It can be seen from the figure that the resistance With the dense distribution of each speed point, considering that there are certain speed fluctuations and resistance fluctuations in the actual vehicle driving, the average value of each speed point data can be taken, and the averaged result curve is fitted with a quadratic term. According to the least squares regression method, Can obtain the estimated value of coefficient A, B, C, as shown in Figure 5 (b), present specific embodiment, actual road resistance curve coefficient least squares estimated value: A=909.42, B=-4.7921, C=0.179 .

The method of the invention can be used for coefficient estimation of the vehicle's actual road resistance curve under various environments and road conditions. On this basis, due to the development of sensor technology, some vehicles already have built-in inertial navigation systems (including GPS, gyroscope, accelerometer, etc.), that is, they can obtain more accurate road slope angle, acceleration, Steering angle and other information, the development of Internet of Vehicles technology also provides the possibility for vehicles to obtain the geographical information of the road ahead in real time, so this invention can also be used for real-time prediction and estimation calculation of actual road resistance. That is, according to the slope information, the slope resistance F _i is obtained, combined with the acceleration and deceleration requirements, as well as the vehicle speed state and the real-time estimated drag coefficients A, B, and C values, the traction demand of the vehicle can be calculated and predicted in real time.

The above detailed description of the method for estimating the actual running resistance of a vehicle with reference to the embodiments is illustrative rather than limiting, and several embodiments can be listed according to the limited scope, so without departing from the general concept of the present invention Changes and modifications should fall within the protection scope of the present invention.

Claims (5)

1. A method for estimating the actual running resistance of a vehicle is characterized by comprising the following steps: the vehicle is driven normally based on an actual road, and the vehicle speed, the engine rotation speed, the torque, the friction torque, the accelerator opening, the gear and the oil injection signal information are collected through a vehicle bus, an external instrument or a built-in sensor of the vehicle when the vehicle runs; the method adopts a GPS, a gyroscope and an accelerometer, or utilizes a vehicle built-in inertial navigation system to collect information of vehicle speed, acceleration, gradient and direction angle, estimates the value of the actual road resistance curve based on the information, combines gradient resistance and acceleration resistance calculation, and estimates the actual road resistance, and comprises the following specific steps:

judging traffic conditions, weather conditions and road conditions to meet the vehicle running environment conditions for carrying out data acquisition;

and step two, judging the vehicle preheating state. Selecting a medium-high speed running vehicle to enable the vehicle to reach a preheating requirement, and enabling the temperature of a cooling liquid of the vehicle and the temperature of engine oil to reach a stable state;

and step three, driving requirements. Selecting a relatively straight actual highway, driving a vehicle by using relatively stable driving behaviors, avoiding rapid acceleration, deceleration and rapid adjustment of driving behaviors of a steering wheel (such as frequent lane change and steering) as much as possible, recording required vehicle operation data in real time, and eliminating corresponding data when the rapid acceleration, deceleration, braking, gear shifting and steering behaviors occur in subsequent calculation without adopting the data;

and step four, data acquisition. In the process of driving the vehicle, the relevant data of the vehicle during running is collected at the collection frequency not lower than 1Hz, and the vehicle speed V, the engine rotating speed n and the engine torque T are collected through the CAN bus of the OBD port of the vehicle _tq Engine friction torque T _m Throttle opening, gear and oil injection signal information; collecting information of vehicle speed, acceleration a, gradient theta or i and direction angle by adopting a GPS, a gyroscope and an accelerometer; selecting a constant-speed driving method or an actual driving speed fragment extraction method to complete data acquisition;

and fifthly, parameter estimation. And (3) carrying out data processing calculation according to the test data obtained in the step four to obtain the resistance curve coefficient estimated value of the actual road of the vehicle.

2. The method for estimating an actual running resistance of a vehicle according to claim 1, characterized in that: the first step of judging traffic conditions, weather conditions and road conditions is carried out under the conditions of no rain, no snow and no fog in weather, and the relative humidity with the temperature of-20 ℃ to 40 ℃ and the humidity of less than 95 percent and the altitude of less than 5000m are applicable; the road traffic index is less than or equal to 2; the wind speed is less than or equal to 2 levels, the ground average wind speed is less than or equal to 3m/s, and the gust is not more than 5m/s.

3. The method for estimating an actual running resistance of a vehicle according to claim 1, characterized in that: and step four, acquiring and calculating actual running data of the vehicle.

Let F _t Represents the driving force of the vehicle, T _tq Representing engine torque, i _g Representing variator ratio, i ₀ Representing the final drive ratio, η representing the mechanical efficiency of the drive train, r representing the wheel radius, the driving force F _t The method comprises the following steps:

if the vehicle slides with gears, the engine stops injecting oil and is in a reverse towing state, and the engine torque T _tq Is negative and is set as T _m Driving force F _t The method comprises the following steps:

wherein the engine torque T _tq And reverse torque T _m The vehicle CAN bus information is acquired and recorded in real time, and the transmission gear ratio i of the transmission _g And final drive ratio i ₀ Acquiring information through a vehicle CAN bus; the wheel radius r selects the static radius value of the wheel.

The relation between the engine speed and the vehicle running speed is:

v is the running speed of the vehicle and is obtained in real time by GPS information or CAN bus information; n is the engine speed, and is obtained in real time by CAN bus information, and the driving force F of the vehicle _t The relation with the engine speed, torque and vehicle speed is:

if the vehicle is in a reverse dragging sliding state with a gear, the formula is as follows:

when the automobile runs on a horizontal road at a constant speed, the rolling resistance from the ground and the air are overcomeAir resistance; let the rolling resistance be F _f Air resistance is F _w When the vehicle runs on the slope, the slope resistance is F _i Acceleration resistance F to be overcome when the vehicle is accelerating _j The vehicle running driving force Ft is the sum of the resistances, namely:

F _t ＝F _f +F _w +F _i +F _j

wherein "F _f +F _w "is a quadratic function of the running speed of the vehicle, namely, is a quadratic function A+B.V+C.V of the standard sliding method ² A resistance value determined by the A, B, C value in ";

ramp resistance F _i The component force generated by the gravity of the vehicle along the ramp is smaller in normal condition when the vehicle runs on the ramp, for example, the maximum longitudinal slope of the micro-hills area of the expressway plain is 3% and the gradient of the mountain heavy hills area of the four-level highway is 9% according to the design rule of the highway route in China. Road grade is expressed as the ratio of the grade height h (in m) to the base length s (in m), namely:

therefore, if the gradient of the road is small, sin θ≡θ=i, then:

F _i ＝M·g·sinθ

wherein M is the mass of the vehicle (unit kg), g is the gravitational acceleration (9.8M/s ² ) The method comprises the steps of carrying out a first treatment on the surface of the θ is the road longitudinal grade angle;

acceleration resistance F _j The inertial force of the vehicle is overcome when the vehicle accelerates and runs. The automobile mass is divided into a translation mass and a rotation mass, and when the automobile accelerates, the translation mass accelerates to generate inertia force, and the rotation mass generates inertia moment.

Wherein m is _r The term rotating mass means that, when the vehicle is traveling in neutral on the road,equivalent effective mass (unit kg), m of all rotating parts and wheels on the vehicle _r Can be obtained from a 3% estimate of the reference mass of the vehicle,

the running acceleration a (unit m/s 2) of the vehicle. The derivation is made from the above formula:

F _t ＝(A+B·V+C·V ² )+M·g·sinθ+(M+m _r ) A, combine with F _t The calculation formula further obtains:

namely:

or, when the belt is in sliding:

4. the method for estimating an actual running resistance of a vehicle according to claim 1, characterized in that: the constant speed driving method in the fourth step is preferably selected as a method for determining the vehicle resistance coefficient A, B, C under relatively straight road conditions and good traffic conditions; the highest test speed is selected according to the actual speed limit of the road and the highest speed limit of the vehicle, the speed is changed gradually from high speed to low speed (or from low to high) with the speed not more than 20km/h until the speed is lower than 20km/h, and the speed is kept stable for a period of time at each speed point to ensure that enough data are acquired. The method comprises the steps of selecting stage data of which the vehicle speed is basically stable and the driver does not carry out rapid acceleration and deceleration, braking and gear shifting and greatly adjusts the driving behavior of the steering wheel as calculation data, obtaining corresponding data points of the vehicle resistance and the vehicle speed V in a second-by-second mode at different vehicle speed stages according to a formula (1), and obtaining a A, B, C value through analysis according to a least square regression method.

5. The method for estimating an actual running resistance of a vehicle according to claim 1, characterized in that: and step four, the actual driving speed fragment extraction method comprises the following steps: in a section of test target road section, the vehicle drives normally according to the actual traffic condition, judges the actual calculation data choice according to the collected data, selects the formula (1) and the formula (2), obtains the corresponding data points of the vehicle resistance and the vehicle speed V every second, and analyzes according to the least square regression method to obtain a A, B, C value.

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