Torque control method of electric vehicle
By creating a baseline acceleration mapping table in pure electric vehicles and adjusting the torque in real time, the problem of insufficient torque regulation of pure electric vehicles under non-full load/heavy load conditions is solved, and a balance between power and safety under different working conditions is achieved.
Patent Information
- Application Number
- CN202510950192.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-10
- Publication Date
- 2025-10-10
AI Technical Summary
Pure electric vehicles have excessive or insufficient driving force under non-full load/heavy load conditions and are unable to effectively adjust torque to reduce collision risks, especially in the absence of acceleration sensors, load and slope detection.
By collecting dynamic parameters under heavy load on flat roads to create a baseline acceleration mapping table, the vehicle acceleration is calculated in real time and compared with the baseline value. The target output torque is adjusted to match the vehicle acceleration level. A two-dimensional lookup table is generated using Kalman filtering for torque compensation, and the torque is dynamically adjusted in combination with the correction coefficient.
Without increasing hardware costs, this system reduces collision risks while ensuring that the vehicle's power under various operating conditions meets the acceleration time benchmark of fuel vehicles, avoiding insufficient power or excessive acceleration.
Smart Images
Figure CN120756307A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of pure electric vehicle drive control, and in particular to a torque control method for an electric vehicle. Background Art
[0002] The torque characteristics of the drive motor of a pure electric vehicle are different from those of the engine of a fuel vehicle. The low-speed torque of the motor of the same level is much greater than the starting torque of the engine. Therefore, under the same operating conditions, the acceleration of electric vehicles is faster than that of fuel vehicles of the same level.
[0003] For pure electric logistics vehicles, the peak driving torque is based on full load / heavy load design, so when the vehicle is in a non-full load / heavy load condition, the driving force is excessive. Under such conditions, electric vehicles that accelerate too quickly are more likely to increase the risk of collision. Therefore, there is a limited torque demand under non-full load / heavy load conditions; for logistics vehicles without acceleration sensors, load and slope detection, it is impossible to directly judge the vehicle load or road conditions to perform dynamic torque adjustment. Therefore, if the torque is directly limited, it will cause insufficient or excessive power for the entire vehicle. Therefore, a motor torque control method is needed to control the acceleration of the vehicle in various working conditions such as climbing, loading, controlling, and descending, so that it can be in a reasonable acceleration time benchmarked against fuel vehicles. This can ensure that the acceleration of the vehicle is not too weak when it is fully loaded or climbing, and can avoid excessive acceleration when the vehicle is unloaded to reduce the probability of collision accidents. Therefore, those skilled in the art provide a torque control method for electric vehicles to solve the problems raised in the above background technology. Summary of the Invention
[0004] An object of the present invention is to provide a torque control method for an electric vehicle to solve the problems raised in the above background technology.
[0005] To achieve the above object, the present invention provides the following technical solutions:
[0006] A torque control method for an electric vehicle comprises the following steps:
[0007] Step S10: Under heavy load on a flat road, collect dynamic parameters and create a corresponding reference acceleration mapping table;
[0008] Step S20: Calculate the real-time acceleration of the vehicle during driving;
[0009] Step S30: Determine the vehicle acceleration level by comparing with the reference value. If the acceleration is lower than the reference value, calculate the torque to be increased based on the acceleration difference to increase the target output torque. If the acceleration is higher than the reference value, calculate the torque to be reduced based on the acceleration difference to reduce the target output torque.
[0010] As a further solution of the present invention: the method for making the reference acceleration in step S10 is: under heavy load on a flat road, collect the vehicle speed and time, and calculate the reference acceleration Where Δv is the change in vehicle speed, and Δt is the change in time. 100 or more sets of valid acceleration data are collected, and a two-dimensional lookup table is generated after Kalman filtering. The calculated values are then made into a mapping table for the VCU to search.
[0011] Among them: under the benchmark working conditions, the vehicle speed range is 10-60Km / h, the load requirement is ≥90% of the rated load, and the road slope is ≤1%.
[0012] As a further solution of the present invention: the method for calculating the real-time acceleration in step S20 is: when the vehicle is running, the speed and time are collected in real time, and the real-time acceleration is calculated. Where Δt=max(10ms,2*T CAN ), T CAN is the bus cycle, typically 20-100ms.
[0013] As a further solution of the present invention: the calculation method of the acceleration difference in step S30 is: Δa=α 基准 -α 实时 .
[0014] As a further solution of the present invention: the calculation method of the torque compensation value in step S30 is: Where T 补偿 is the torque value that needs to be compensated, T 实时 is the actual output torque, i is the transmission system reduction ratio, and the value for commercial vehicles is 6-12.
[0015] As a further solution of the present invention, the method for compensating the output torque in step S30 includes the following steps:
[0016] Step a: When the compensation torque is 0±Nm, there is no need to adjust the target torque;
[0017] Step b: When the compensation torque is positive, T 校正 =T 补偿 *k1, where k1 is the correction factor, and the value range of k1 when overloaded or climbing is 0.3-0.9;
[0018] Step c: When the compensation torque is negative, if the actual output torque is ≤ 0 N.m, T 校正 =0; if the actual output torque is greater than 0N.m, T 校正 =T 补偿 *k2, where k2 is the correction factor; the value range of k2 when no-load or downhill is 0.5-0.8.
[0019] As a further scheme of the present application: the calculation formula of the target output torque is: T 目标 = T 校正 + T 实时 When T 目标 > T 峰值 , the target torque is output according to the peak torque.
[0020] As a further scheme of the present application: the collection conditions of the vehicle speed and the time include the vehicle model parameters, the road conditions, the load and the data collection period.
[0021] As a further scheme of the present application: the correction coefficients k1 and k2 are determined according to the smoothness requirement and the specific vehicle parameters.
[0022] As a further scheme of the present application: the electric vehicle is a pure electric logistics vehicle.
[0023] Compared with the prior art, the present application has the beneficial effects that:
[0024] 1. The present application calculates the real-time acceleration of the whole vehicle and compares it with the reference value to determine the acceleration level of the whole vehicle, and if the acceleration is lower than the reference value, the target output torque is increased, and if the acceleration is higher than the reference value, the target output torque is decreased. After adding this algorithm, the collision risk (limiting torque) can be reduced, and the vehicle power can be ensured without increasing the hardware cost.
[0025] 2. Under the condition of heavy load on a flat road, the power performance parameters are collected, and the corresponding reference acceleration mapping table is made. The real-time acceleration of the whole vehicle is calculated during the driving process, and the reference value is compared to determine the acceleration level of the whole vehicle. If the acceleration is lower than the reference value, the torque that needs to be increased is calculated according to the acceleration difference, and the target output torque is increased. If the acceleration is higher than the reference value, the torque that needs to be reduced is calculated according to the acceleration difference, and the target output torque is decreased. BRIEF DESCRIPTION OF DRAWINGS
[0026] Figure 1 The flowchart of the present application. DETAILED DESCRIPTION
[0027] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all the other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.
[0028] Please refer to Figure 1 , a torque control method of an electric vehicle, comprising the following steps:
[0029] Step S10: Under heavy load on a flat road, collect dynamic parameters and create a corresponding reference acceleration mapping table;
[0030] Step S20: Calculate the real-time acceleration of the vehicle during driving;
[0031] Step S30: Determine the vehicle acceleration level by comparing with the reference value. If the acceleration is lower than the reference value, calculate the torque to be increased based on the acceleration difference to increase the target output torque. If the acceleration is higher than the reference value, calculate the torque to be reduced based on the acceleration difference to reduce the target output torque.
[0032] The method for making the reference acceleration in step S10 is as follows: under heavy load on a flat road, collect vehicle speed and time, and calculate the reference acceleration Where Δv is the change in vehicle speed, and Δt is the change in time. 100 or more sets of valid acceleration data are collected, and a two-dimensional lookup table is generated after Kalman filtering. The calculated values are then made into a mapping table for the VCU to search.
[0033] Among them: under the benchmark working conditions, the vehicle speed range is 10-60Km / h, the load requirement is ≥90% of the rated load, and the road slope is ≤1%.
[0034] The method for calculating the real-time acceleration in step S20 is as follows: when the vehicle is running, the speed and time are collected in real time, and the real-time acceleration is calculated. Where Δt=max(10ms,2*T CAN ), T CAN is the bus cycle, typically 20-100ms.
[0035] The calculation method of the acceleration difference in step S30 is: Δa=α 基准 -α 实时 .
[0036] The calculation method of the torque compensation value in step S30 is: Where T 补偿 is the torque value that needs to be compensated, T 实时 is the actual output torque, i is the transmission system reduction ratio, and the value for commercial vehicles is 6-12.
[0037] The method for outputting torque compensation in step S30 includes the following steps:
[0038] Step a: When the compensation torque is 0±Nm, there is no need to adjust the target torque;
[0039] Step b: When the compensation torque is positive, T 校正 =T 补偿*k1, where k1 is the correction factor, and the value range of k1 when overloaded or climbing is 0.3-0.9;
[0040] Step c: When the compensation torque is negative, if the actual output torque is ≤ 0 N.m, T 校正 =0; if the actual output torque is greater than 0N.m, T 校正 =T 补偿 *k2, where k2 is the correction factor; the value range of k2 when no-load or downhill is 0.5-0.8.
[0041] The target output torque is calculated as follows: T 目标 =T 校正 +T 实时 , when T 目标 >T 峰值 , the target torque is output according to the peak torque.
[0042] The conditions for collecting vehicle speed and time include: vehicle model parameters, road conditions, load and data collection cycle.
[0043] The correction coefficients k1 and k2 are determined according to ride comfort requirements and specific vehicle parameters.
[0044] Among them, the electric vehicle is a pure electric logistics vehicle.
[0045] Example 1: Torque adjustment under heavy load conditions on flat roads
[0046] 1. Basic parameters
[0047] Vehicle parameters: 4.5-ton pure electric logistics vehicle, motor peak torque, reduction ratio i=8.2.
[0048] Road conditions: Level asphalt road surface.
[0049] Load: Cargo weight 4.5 tons (fully loaded).
[0050] Data acquisition cycle: Δt = 50ms (based on CAN signal refresh rate, T CAN =25m, t=max(10ms,2*25ms)=50ms).
[0051] 2. Benchmark acceleration production
[0052] The time Δt=8.2s for the vehicle to accelerate from 20 km / h to 50 km / h is collected.
[0053] Calculate the base acceleration: 150 sets of valid acceleration data are collected and Kalman filtered to generate a vehicle speed-acceleration reference mapping table, which is stored in the VCU. Some of the mapping table data are as follows:
[0054] Vehicle speed (km / h) <![CDATA[基准加速度(m / s 2 )]]> 20 0.95 25 0.96 30 0.97 35 0.98 40 0.98 45 0.97 50 0.96
[0055] 3. Real-time torque adjustment process
[0056] 1. When the vehicle is actually running, the real-time speed at a certain moment accelerates from 30km / h to 35km / h, and the time interval Δt = 50ms is used to calculate the real-time acceleration:
[0057]
[0058] (The data here is abnormal. It should actually be the change in vehicle speed over a certain period of time. Recalculate: assume that the vehicle accelerates from 30km / h to 35km / h in 5s).
[0059]
[0060] 2. Acceleration difference:
[0061] Δα=α 基准 -α 实时 =0.98-0.278=0.702m / s 2
[0062] 3. Actual output torque: T 实时 =200N·m.
[0063] 4. Compensation torque:
[0064]
[0065] 5. Torque correction: Assume the correction coefficient k1 = 0.6, then:
[0066] T 校正 =T 补偿 *k1=64.69*0.6≈37.01N·m
[0067] 6. Target output torque:
[0068] T 目标 =T 校正 +T 实时 =37.01+200=237.01N·m
[0069] Due to T 目标 =237.01N·m <T 峰值 =350N·m, so the target torque is output as 237.01N·m.
[0070] 4. Verification Data and Results
[0071] The vehicle acceleration before adjustment is 0.278m / s 2After adjustment, the target torque output is 237.01N·m, and the actual measured vehicle acceleration is increased to 0.68m / s 2 , close to the baseline acceleration of 0.98m / s 2 , the dynamic performance has been significantly improved.
[0072] Under this operating condition, the vehicle's acceleration performance is improved and there is no over-acceleration, which verifies the effectiveness of this torque control method under heavy-load conditions on flat roads.
[0073] Example 2: Torque adjustment under no-load downhill conditions
[0074] 1. Basic parameters
[0075] 1. Vehicle parameters: 4.5-ton pure electric logistics vehicle, motor peak torque T 峰值 =350N·m, reduction ratio i=8.2.
[0076] 2. Road conditions: Downhill section with a slope of about 5°.
[0077] 3. Load: No load.
[0078] 4. Data acquisition period: Δt = 50ms.
[0079] 2. Benchmark acceleration production
[0080] Same as Example 1, reference acceleration reference.
[0081] 3. Real-time torque adjustment process
[0082] 1. A vehicle is traveling downhill and its real-time speed increases from 30 km / h to 35 km / h over a time interval of Δt = 5 seconds. Calculate the real-time acceleration:
[0083] △v 实时 =35-30=5km / h=5 / 3.6≈1.389m / s
[0084]
[0085] 2. Acceleration difference:
[0086] Δa=a 基准 -a 实时 =0.98-0.278=0.702m / s 2
[0087] 3. Actual output torque:
[0088] T 实时 =-50N·m
[0089] (The vehicle is on a downhill slope, the motor is in a power generation state, and outputs negative torque).
[0090] 4. Compensation torque:
[0091]
[0092] 5. Since the compensation torque is negative and the actual output torque T 实时 =-50N·m≤0N·m, the vehicle is judged to be in downhill condition. After correction:
[0093] T 校正 =0
[0094] 6. Target output torque:
[0095] T 目标 =T 校正 +T 实时 =0+(-50)=-50N·m
[0096] That is, the target torque maintains the actual output torque -50N·m unchanged.
[0097] 4. Verification Data and Results
[0098] 1. The vehicle acceleration before adjustment is 0.278m / s 2 After adjustment, the target torque remains at -50 N·m, and the actual measured vehicle acceleration is 0.28 m / s 2 , which is basically the same as before adjustment, avoiding the situation where the vehicle accelerates too fast in downhill conditions.
[0099] 2. Under this operating condition, the vehicle acceleration is effectively controlled, verifying the effectiveness of the torque control method under downhill conditions.
[0100] Example 3: Torque adjustment under half-load flat road conditions
[0101] 1. Basic parameters
[0102] 1. Vehicle parameters: 4.5-ton pure electric logistics vehicle, motor peak torque T 峰值 =350N·m, reduction ratio i=8.2.
[0103] 2. Road conditions: level asphalt road surface.
[0104] 3. Load: Cargo weight 2.25 tons (half load).
[0105] 4. Data acquisition period: Δt = 50ms.
[0106] 2. Benchmark acceleration production
[0107] Same as in Example 1, the reference acceleration α 基准 =0.98m / s 2 .
[0108] 3. Real-time torque adjustment process
[0109] 1. A vehicle is traveling on a half-loaded flat road. The real-time speed increases from 20 km / h to 25 km / h over a time interval of Δt = 3 seconds. Calculate the real-time acceleration:
[0110] Δv 实时 =25-20=5km / h=5 / 3.6≈1.389m / s
[0111]
[0112] 2. Acceleration difference:
[0113] Δa=a 基准 -a 实时 =0.98-0.463=0.517m / s 2
[0114] 3. Actual output torque:
[0115] T 实时 =150N·m.
[0116] 4. Compensation torque:
[0117]
[0118] 5. Torque correction: Assume the correction coefficient k2 = 0.8, then:
[0119] T 校正 =T 补偿 *k2=20.41*0.8≈16.33Nm
[0120] 6. Target output torque:
[0121] T 目标 =T 校正 +T 实时 =16.33+150=166.33Nm
[0122] Due to T 目标 =166.33N·m <T 峰值 =350N·m, so the target torque is output as 166.33N·m.
[0123] 4. Verification Data and Results
[0124] 1. The vehicle acceleration before adjustment is 0.463m / s 2 After adjustment, the target torque output is 166.33N·m, and the actual measured vehicle acceleration is increased to 0.72m / s 2 , close to the baseline acceleration of 0.98m / s2 , the power is improved while avoiding over-acceleration.
[0125] 2. Under this operating condition, the vehicle acceleration performance is reasonably improved, verifying the effectiveness of the torque control method under half-load flat road conditions.
[0126] Example 4: Comparative experiments under different load conditions
[0127] 1. Experimental Purpose
[0128] Verify the impact of this torque control method on vehicle dynamics and safety under different load conditions.
[0129] 2. Experimental Parameters
[0130] 1. Vehicle parameters: 4.5-ton pure electric logistics vehicle, motor peak torque T 峰值 =350m·m, reduction ratio i=8.2.
[0131] 2. Road conditions: level asphalt road surface.
[0132] 3. Load: empty, half load (2.25 tons), full load (4.5 tons).
[0133] 4. Data acquisition period: Δt = 50ms.
[0134] 3. Experimental Process
[0135] 1. Accelerate the vehicle from a standstill to 50 km / h under no-load, half-load, and full-load conditions, and record the acceleration time and maximum acceleration.
[0136] 2. Use this torque control method to adjust the torque, repeat the above acceleration process, and record the acceleration time and maximum acceleration.
[0137] 4. Experimental data and results
[0138] Load conditions Whether to use torque control method Acceleration time (s) Maximum acceleration (m / s2) No load no 6.5 1.2 No load yes 7.8 0.95 Half a load no 8.2 1.0 Half a load yes 9.0 0.98 fully loaded no 10.5 0.8 fully loaded yes 10.0 0.95
[0139] 5. Results Analysis
[0140] 1. Under no-load conditions, without the torque control method, the vehicle's acceleration time is short and the maximum acceleration is high, posing a risk of overacceleration. With the torque control method, the acceleration time is extended and the maximum acceleration is reduced to near the baseline acceleration, effectively reducing the risk of collision.
[0141] 2. Under half-load and full-load conditions, the use of this torque control method shortens the acceleration time and increases the maximum acceleration, indicating that the vehicle's dynamic performance has been improved.
[0142] 3. Experimental data shows that this torque control method can dynamically adjust the output torque according to different load conditions, reduce the risk of overacceleration when unloaded, and improve the vehicle's dynamics when half-loaded and fully loaded, verifying the effectiveness and practicality of this method.
[0143] This algorithm calculates the vehicle's real-time acceleration and compares it with a baseline value to determine the vehicle's acceleration level. If the acceleration is below the baseline, the target output torque is increased; if it is above the baseline, the target output torque is reduced. This algorithm reduces collision risk (by limiting torque) while ensuring vehicle dynamics without increasing hardware costs (adding an acceleration sensor, ramp, and load sensor would cost approximately 1,500 RMB).
[0144] Under heavy load on flat roads, dynamic parameters are collected and a corresponding benchmark acceleration mapping table is created. The real-time acceleration of the vehicle is calculated during actual driving and compared with the benchmark value to determine the acceleration level of the vehicle. If the acceleration is lower than the benchmark value, the torque that needs to be increased is calculated based on the acceleration difference to increase the target output torque. If the acceleration is higher than the benchmark value, the torque that needs to be reduced is calculated based on the acceleration difference to reduce the target output torque.
[0145] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.
Claims
1. A torque control method for an electric vehicle, characterized in that: The following steps are involved: Step S10: Under heavy load on a flat road, collect dynamic parameters and create a corresponding reference acceleration mapping table; Step S20: Calculate the real-time acceleration of the vehicle during driving; Step S30: Determine the vehicle acceleration level by comparing with the reference value. If the acceleration is lower than the reference value, calculate the torque to be increased based on the acceleration difference to increase the target output torque. If the acceleration is higher than the reference value, calculate the torque to be reduced based on the acceleration difference to reduce the target output torque.
2. The torque control method for an electric vehicle according to claim 1, characterized in that: The method for making the reference acceleration in step S10 is: under heavy load on a flat road, collect vehicle speed and time, and calculate the reference acceleration Where Δv is the change in vehicle speed, and Δt is the change in time; Collect ≥100 sets of valid acceleration data, generate a two-dimensional lookup table after Kalman filtering, and make the calculated values into a mapping table for VCU to search; Among them: under the benchmark working conditions, the vehicle speed range is 10-60Km / h, the load requirement is ≥90% of the rated load, and the road slope is ≤1%.
3. The torque control method for an electric vehicle according to claim 1, characterized in that: The method for calculating the real-time acceleration in step S20 is: when the vehicle is running, the vehicle speed and time are collected in real time, and the real-time acceleration is calculated. Where Δt=max(10ms,2*T CAN ), T CAN is the bus cycle, typically 20-100ms.
4. The torque control method for an electric vehicle according to claim 1, characterized in that: The calculation method of the acceleration difference in step S30 is: Δa=α 基准 -α 实时 .
5. The torque control method for an electric vehicle according to claim 1, characterized in that: The calculation method of the torque compensation value in step S30 is: Where T 补偿 is the torque value that needs to be compensated, T 实时 is the actual output torque, i is the transmission system reduction ratio, and the value for commercial vehicles is 6-12.
6. The torque control method for an electric vehicle according to claim 1, characterized in that: The method for output torque compensation in step S30 includes the following steps: Step a: When the compensation torque is 0±Nm, there is no need to adjust the target torque; Step b: When the compensation torque is positive, T 校正 =T 补偿 *k1, where k1 is the correction factor, and the value range of k1 when overloaded or climbing is 0.3-0.9; Step c: When the compensation torque is negative, if the actual output torque is ≤ 0 N.m, T 校正 =0; if the actual output torque is greater than 0N.m, T 校正 =T 补偿 *k2, where k2 is the correction factor; the value range of k2 when no-load or downhill is 0.5-0.
8.
7. The torque control method for an electric vehicle according to claim 6, characterized in that: The target output torque is calculated as follows: T 目标 =T 校正 +T 实时 , when T 目标 >T 峰值 , the target torque is output according to the peak torque.
8. The torque control method for an electric vehicle according to claim 1, characterized in that: The conditions for collecting vehicle speed and time include: vehicle model parameters, road conditions, load and data collection cycle.
9. The torque control method for an electric vehicle according to claim 1, characterized in that: The correction coefficients k1 and k2 are determined according to the ride comfort requirements and specific vehicle parameters.
10. The torque control method for an electric vehicle according to any one of claims 1 to 9, characterized in that: The electric vehicle is a pure electric logistics vehicle.