Drive control method for electric vehicle and electric vehicle

Abstract

The invention provides a driving control method of an electric vehicle and the electric vehicle, and relates to the field of vehicle electric control. The method comprises the following steps: acquiring target rotating speeds, feedback currents, feedback rotating speeds and feedback torques of left and right motors; determining working conditions according to the target rotating speed and the feedback rotating speed; in the first working condition, if the feed-forward starting condition is not met, the feed-forward torque is set to be zero, and if the feed-forward starting condition is met, the feed-forward torque is calculated according to the target rotating speed, the feedback rotating speed and the feedback torque, and the feed-forward torque is superposed to the PID output end of the speed loop to serve as the additional input of the current loop; and in the second working condition, calculating a synchronous adjustment torque according to the target rotating speed, the feedback current and the feedback rotating speed, and fusing the synchronous adjustment torque with a feedforward torque calculated in the previous first working condition to obtain a final output torque to drive the left and right motors. According to the scheme, the dual requirements of the independent drive vehicle for rapid dynamic response and high-steady-state synchronization precision under the complex working condition that the load is variable and suddenly changed can be met.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of vehicle electric control, in particular to a driving control method of an electric vehicle and the electric vehicle. BACKGROUND

[0002] In the field of electric vehicles, especially special operation vehicles such as riding mowers, in order to improve the flexibility of operation and the adaptability to terrain, a configuration of driving left and right wheels by independent motors is often adopted. However, for example, in the case of riding mowers, when working on complex terrains such as slopes and wet grasslands, the load difference between the left and right wheels is large and the mutation is strong due to high-frequency events such as "single-side grass pressing", which easily causes the rotation speed to be out of sync, causing the vehicle to deviate and the trajectory to be not straight, seriously affecting the operation efficiency and the safety of operation.

[0003] In view of this problem, the commonly used solution in the industry at present is a double-wheel synchronization control scheme based on speed loop PID feedback or simple master-slave type. This kind of prior art mainly compares the speed deviation of the left and right wheels in real time, and uses a PID controller to calculate and output a compensation torque. However, these conventional schemes are extremely prone to slow response in the working conditions that require rapid synchronization establishment (such as hill starting), and problems such as starting weakness or single-side lagging. At the same time, when the resistance of one side of the wheel increases due to grass pressing, skidding, etc., the synchronization accuracy is easily reduced or even fails, and the vehicle deviates during driving.

[0004] Therefore, the existing synchronization scheme based on conventional PID or master-slave control is difficult to meet the dual requirements of fast dynamic response and high steady-state synchronization accuracy of independent driving vehicles in complex working conditions with variable and sudden load, and a more optimal solution is urgently needed. SUMMARY

[0005] The purpose of the present application is to provide a driving control method of an electric vehicle and the electric vehicle, which can meet the dual requirements of fast dynamic response and high steady-state synchronization accuracy of independent driving vehicles in complex working conditions with variable and sudden load.

[0006] The present application is implemented as follows: In a first aspect, this application provides a drive control method for an electric vehicle, wherein the left and right drive wheels of the electric vehicle are driven independently by left and right motors. The method includes the following steps: acquiring the target speed, feedback current, feedback speed, and feedback torque of the left and right motors; determining the operating condition of the electric vehicle based on the target speed and feedback speed to obtain current operating condition information; when the current operating condition information indicates that the electric vehicle is in a first operating condition, if the feedforward start condition is not met, the feedforward torque is set to zero; if the feedforward start condition is met, the feedforward torque is calculated based on the target speed, feedback speed, and feedback torque, and the calculated feedforward torque is superimposed on the output of the speed loop PID as an additional input to the current loop; when the current operating condition information indicates that the electric vehicle is in a second operating condition, the synchronization adjustment torque is calculated based on the target speed, feedback current, and feedback speed to obtain the synchronization adjustment torque, and the synchronization adjustment torque is fused with the feedforward torque calculated under the previous first operating condition to obtain the final output torque for driving the left and right motors.

[0007] In a second aspect, this application provides an electric vehicle comprising a memory for storing one or more programs; a processor; and, when the one or more programs are executed by the processor, implementing the method as described in any one of the first aspects above.

[0008] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in any one of the first aspects above.

[0009] Fourthly, this application provides a computer program product including computer program instructions that, when executed by a processor, implement the method as described in any one of the first aspects above.

[0010] Compared with the prior art, this application has at least the following advantages or beneficial effects: This application proposes a drive control method for electric vehicles. It first acquires vehicle operating state parameters in real time and identifies whether the current operating condition requires rapid synchronization (dynamic) or high-precision synchronization (steady-state). When identified as a dynamic condition (such as starting or accelerating), after meeting specific conditions, it directly calculates the feedforward compensation torque based on the target speed, feedback speed, and current actual load torque, and quickly superimposes it onto the output of the traditional speed loop. This feedforward channel bypasses the integral lag of traditional PID control, enabling near-instantaneous torque compensation for sudden load changes, thus solving the problem of slow dynamic response.

[0011] Next, once the vehicle enters steady-state operation, it switches to a synchronization adjustment mode based on feedback current and speed. The adjustment torque calculated in this mode does not act independently but is integrated with the feedforward torque generated in the previous dynamic condition to form the final output. This design not only ensures a smooth transition from dynamic to steady-state operation, avoiding the shock of mode switching, but also allows the rapid response advantage established during the dynamic process to be "remembered" and carried over to steady-state adjustment, thereby synergistically improving the dynamic performance and steady-state accuracy of the synchronization control throughout the entire operating cycle.

[0012] That is, this application effectively overcomes the inherent shortcomings of traditional single feedback control mode in terms of response lag and insufficient accuracy by adaptively coordinating feedforward and feedback modes according to the working conditions without changing the hardware architecture. This results in an overall synergistic improvement in the response speed and steady-state accuracy of electric vehicle drive control. Attached Figure Description

[0013] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a flowchart of an embodiment of a drive control method for an electric vehicle according to this application; Figure 2 This is a flowchart illustrating the steps for calculating the synchronous adjustment torque in one embodiment of this application. Figure 3 This is a flowchart of yet another embodiment of a drive control method for an electric vehicle according to this application; Figure 4 This is a structural block diagram of an electric vehicle provided in an embodiment of this application.

[0015] Icons: 201, Processor; 202, Memory; 203, Communication Interface. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. It should be understood that this application is not limited to the exemplary embodiments described herein.

[0017] In this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, without necessarily requiring or implying any such actual relationship or order between these entities or operations.

[0018] Summary of the application For electric vehicles with independent motors driving the left and right drive wheels, the current mainstream synchronization control schemes rely on traditional PID feedback or simple master-slave control structures. These schemes mainly achieve synchronization by comparing the speed deviations of the left and right wheels in real time and using the PID controller to generate compensation torque.

[0019] In developing this application, the inventors discovered that existing conventional solutions are prone to dynamic response lag because during start-up, acceleration, or sudden load changes, the reliance on integral accumulation leads to slow synchronization establishment, resulting in weak start-up or unilateral lag. Secondly, their fixed control parameters cannot detect real-time load differences, making it difficult to provide accurate differential compensation during sudden load changes, thus causing synchronization failure.

[0020] To address the aforementioned technical problems, this application provides a drive control method for electric vehicles. Without altering the hardware architecture, it distinguishes between a large-error "dynamic condition" requiring rapid response and a small-error "steady-state condition" requiring fine adjustment by using the target and feedback speeds of the left and right motors. In the dynamic condition, a feedforward channel based on real-time load torque is introduced to bypass the traditional PID integral lag, achieving rapid torque compensation to improve transient response. Upon entering the steady-state condition, feedback regulation emphasizing precise synchronization is initiated, and the feedforward torque generated in the previous dynamic condition is intelligently integrated with it for joint output. This design not only ensures dynamic performance but also achieves smooth transitions and complementary advantages between modes through a torque fusion mechanism, thereby synergistically improving the overall response speed and steady-state accuracy of the electric vehicle drive control.

[0021] After introducing the basic principles of this application, various non-limiting embodiments of this application will be described in detail below with reference to the accompanying drawings. Unless otherwise specified, the various embodiments and features described below can be combined with each other.

[0022] It should be noted that the electric vehicle drive control method of this application is mainly applicable to various electric wheeled vehicles or mobile platforms that use independent motors for the left and right wheels and have high requirements for dynamic response and synchronization accuracy under complex asymmetrical load conditions. This includes, but is not limited to, ride-on lawnmowers, electric tractors, engineering loading and unloading equipment, special AGVs, aerial work platforms, and all-terrain vehicles for the disabled.

[0023] To ensure a consistent and clear explanation in the following text, this application will select a "riding lawnmower" as a typical application example of the method for detailed description. Riding lawnmowers commonly face complex working conditions in lawn operations, such as slopes, slippery surfaces, and "one-sided grass pressing," and their technical requirements are highly consistent with the technical problems to be solved in this application, facilitating understanding of the technical solution and advantages of this application by those skilled in the art.

[0024] Exemplary method Please see Figure 1 This is a drive control method for an electric vehicle, wherein the left and right drive wheels of the electric vehicle are independently driven by left and right motors. The method includes the following steps: Step S101: Obtain the target speed, feedback current, feedback speed, and feedback torque of the left and right motors.

[0025] In step S101 above, the target speed is data from the upper-level controller (such as the vehicle controller), representing the driver's operating intention or the target speed output by the controller. The feedback current and feedback speed (usually from the encoder) are data fed back in real time by the motor driver. The feedback torque is typically derived from the feedback current based on the motor torque constant, directly reflecting the actual load the motor is currently overcoming. Acquiring this data provides a raw, synchronous data foundation for subsequent judgments and calculations.

[0026] For example, to suppress noise and obtain smoother data, the feedback speed can be filtered using a Butterworth low-pass filter to eliminate high-frequency noise interference. The feedback current is then low-pass filtered, and the current signal is converted into a feedback torque value based on the known motor torque constant.

[0027] Step S102: Determine the operating condition of the electric vehicle based on the target speed and the feedback speed, and obtain the current operating condition information.

[0028] In step S102 above, the deviation (or relative deviation) between the target speed and the feedback speed is calculated by comparing the two. Based on the magnitude of this deviation (usually compared with a preset threshold), the vehicle's operating state is intelligently divided into: (1) First operating condition: corresponding to situations with large speed errors, such as dynamic processes like vehicle start-up, rapid acceleration, and sudden load encounters. At this time, the primary task is to quickly eliminate large errors and establish synchronization. (2) Second operating condition: corresponding to situations with small speed errors, such as steady-state or quasi-steady-state processes like uniform vehicle speed driving and smooth steering. At this time, the primary task is to maintain high-precision speed following and synchronization.

[0029] In other words, by determining the operating conditions of the electric vehicle and then deciding whether to proceed to step 103 or step 104, a precise match between the control strategy and the operating conditions is achieved. This avoids the use of sluggish pure integral regulation when a fast response is required, and also avoids the use of feedforward shocks that may cause overshoot when fine regulation is required, thus ensuring the optimization of overall performance from the system architecture perspective.

[0030] Step S103: When the current operating condition information indicates that the electric vehicle is in the first operating condition, if the feedforward start condition is not met, the feedforward torque is set to zero. If the feedforward start condition is met, the feedforward torque is calculated based on the target speed, feedback speed and feedback torque, and the calculated feedforward torque is superimposed on the output of the speed loop PID as an additional input to the current loop.

[0031] When the current operating condition information indicates that the electric vehicle is in the first operating condition (dynamic condition or large error condition), step S103 is activated. It first determines whether the detailed conditions for feedforward activation (such as directional consistency) are met. If met, the feedforward torque is quickly calculated using the target speed, feedback speed, and crucial feedback torque via a feedforward algorithm. If not met, no further calculation is performed, and the feedforward torque is directly set to zero. This calculation process is essentially a predictive compensation: the feedback torque reflects the current load, while the speed error trend indicates the direction and urgency of compensation. The calculated feedforward torque is directly superimposed on the output of the speed loop PID controller.

[0032] The feedforward torque generated in step S103 has the following main functions: First, within the current control cycle, it immediately merges with the feedback torque output by the speed loop PID, serving together as an instruction to the current loop, thereby significantly improving the transient response speed. Second, this feedforward torque, as a continuous or gradually decreasing variable, is transmitted and used for torque fusion in step 104, realizing the transmission of dynamic process information to the steady-state process.

[0033] In other words, in step S103 above, the sluggishness of the speed loop PID integrator is bypassed by the feedforward channel, which can provide timely torque compensation at the moment of load change or start-up, effectively eliminating the phenomena of "weak start-up" and "one-sided lag", and significantly improving the vehicle's synchronization establishment speed and handling under dynamic conditions.

[0034] Step S104: When the current working condition information indicates that the electric vehicle is in the second working condition, the synchronous adjustment torque is calculated based on the target speed, feedback current and feedback speed to obtain the synchronous adjustment torque. The synchronous adjustment torque is then fused with the feedforward torque calculated under the previous first working condition to obtain the final output torque that drives the left and right motors.

[0035] When the current operating condition information indicates that the electric vehicle is in the second operating condition (steady-state condition or small-error condition), the synchronization adjustment torque is calculated based on the target speed, feedback current, and feedback speed. This calculation focuses on finely correcting the speed synchronization relationship between the left and right wheels through feedback adjustment (especially by introducing feedback current to sense load differences). Subsequently, the synchronization adjustment torque calculated in step S104 is superimposed and fused with the feedforward torque calculated and possibly maintained from the previous first operating condition (the previous dynamic operating condition before the steady-state condition) to form the final output torque.

[0036] Among them, the synchronous adjustment torque ensures high-precision synchronization and load adaptation potential under steady state; while the fusion of historical feedforward torque realizes the following functions: (1) Smooth transition: when the electric vehicle drive control process switches from dynamic mode to steady state mode, the output torque will not change by a step, avoiding vehicle body shaking; (2) Inheritance optimization: the beneficial compensation effect generated in the dynamic response stage is continued in the steady state adjustment as the starting point for steady state control optimization.

[0037] In other words, in step S104 above, the comfort and stability of mode switching are ensured through the fusion mechanism, and the combination of the rapidity of feedforward and the accuracy of feedback enables the vehicle to maintain extremely high synchronization accuracy during steady-state driving, effectively preventing "driving deviation" and improving the overall adaptability and robustness of electric vehicle drive control to different load conditions.

[0038] It should be noted that steps 103 and 104 are not simply linear execution relationships, but rather two parallel and coordinated execution paths that perform torque calculations for dynamic and steady-state conditions respectively, and are coupled across cycles through the key variable of "feedforward torque".

[0039] In summary, this application first acquires target and feedback data, and then classifies the operating conditions into "first operating condition" (large error dynamic operating condition, such as starting or sudden load change) and "second operating condition" (small error steady-state operating condition) based on the magnitude of the speed deviation. Under the first operating condition, when conditions such as directional consistency are met, this application calculates the feedforward compensation torque based on the current speed error and real-time feedback torque, and directly superimposes it onto the output of the speed loop PID controller. This bypasses the lag of traditional PID integrators, achieving near-instantaneous compensation for sudden load changes, thereby significantly improving the problems of weak starting and unilateral lag. Therefore, when starting on a slope or encountering resistance on one side, the electric vehicle drive control operation can quickly output additional drive torque, effectively solving the problems of "weak starting" and "unilateral lag" caused by slow response in existing technologies, and significantly accelerating the process of establishing vehicle dynamic synchronization.

[0040] In the second operating condition, this application calculates the synchronization adjustment torque, which focuses on fine-grained synchronization adjustment, and integrates it with the feedforward torque generated in the previous first operating condition to form the final output. This unique fusion mechanism ensures a smooth and shock-free mode transition from dynamic to steady-state, and intelligently extends the compensation effect of the dynamic response phase to the steady-state adjustment, forming a complementary advantage of feedforward and feedback. This not only guarantees the smoothness and continuity of the control strategy when switching from "fast response" mode to "high-precision synchronization" mode, avoiding vehicle vibration caused by mode jumps, but also improves driving comfort and the stability of electric vehicle drive control operation. Furthermore, by using the synchronization state established in the dynamic response phase as the optimization starting point for steady-state adjustment, the electric vehicle drive control operation can coordinate response speed and adjustment accuracy throughout the entire operating cycle, thereby maintaining higher synchronization reliability under all operating conditions and effectively preventing vehicle deviation under complex loads.

[0041] In other words, under dynamic operating conditions, this application significantly improves the response speed of synchronization establishment through the feedforward channel; under steady-state operating conditions, the fusion of feedforward and feedback ensures high-precision synchronization while achieving smooth and stable control throughout the entire operating process. Ultimately, this application effectively solves the inherent technical contradiction of response lag and insufficient synchronization accuracy caused by traditional single feedback control in independently driven vehicles under complex load conditions.

[0042] To facilitate a better understanding of "feedforward starting conditions" for those skilled in the art, a ride-on lawnmower will be used as an example for further explanation. Taking a ride-on lawnmower as an example, under conditions of large error, such as starting from a slope, accelerating under heavy load (e.g., just entering a deep grassy area), or encountering a sudden increase in resistance on one side of the grass, traditional feedback control suffers from integral accumulation lag, making it difficult to achieve a rapid response and easily leading to weak starting or unilateral lag. Therefore, this application introduces a torque feedforward control mechanism. This mechanism is specifically designed for the frequent start-stop and load changes of lawnmowers in complex lawn environments. By predicting the required compensation torque, it significantly improves the dynamic performance of the system, ensuring smooth starting of the vehicle under various operating conditions.

[0043] Therefore, to prevent rapid oscillations in the data system caused by direct torque superposition, this application adds conditional restrictions to the feedforward control activation, determining whether further feedforward calculations are necessary based on these restrictions. That is, when the current operating condition information indicates the electric vehicle is in its first operating condition, it is necessary to further determine whether the feedforward activation condition is met. If it is met, further calculations will be performed. For example, in some implementations of this application, the feedforward activation condition is that the target speed and the feedback speed are in the same direction. If the directions are opposite (e.g., the target is forward but the vehicle is rolling backward due to a slope), feedforward is prohibited. For example, the target speed and the feedback speed can be directly multiplied; if the result is greater than 0, it indicates that the directions are the same, and the motor is in a controllable acceleration or steady-speed operation phase.

[0044] It's important to note that feedforward is essentially a predictive "boost" compensation. The additional boost is only meaningful and controllable when the motor has already attempted to drive in the target direction. Activating feedforward in a runaway state in the opposite direction will exacerbate system instability and may even trigger mechanical shocks. Therefore, this condition effectively prevents feedforward from being falsely triggered under incorrect operating conditions, avoiding potential driving hazards and improving the safety and reliability of the entire control system.

[0045] Based on the aforementioned scheme, in some implementations of this application, the step of determining the operating condition of the electric vehicle according to the target speed and the feedback speed includes: calculating the relative speed deviation between the target speed and the feedback speed, and determining the operating condition of the electric vehicle according to the comparison relationship between the relative speed deviation and a preset activation threshold. If the absolute value of the relative speed deviation is greater than the preset activation threshold, the operating condition of the electric vehicle is determined to be the first operating condition; otherwise, the operating condition of the electric vehicle is determined to be the second operating condition.

[0046] In the above implementation, a preset activation threshold is introduced to quantify the operating conditions of the electric vehicle. This preset activation threshold can be flexibly configured according to vehicle model or load characteristics, thereby enabling adaptation to different types of independently driven vehicles, from light to heavy loads and from low to high speeds.

[0047] For example, in some implementations of this application, the formula for calculating the relative velocity deviation is: ; in, , For relative speed deviation, For the target speed, For feedback of rotational speed, The preset reference speed threshold is greater than zero. To output the maximum value among the comparison parameters, This outputs the minimum value among the comparison parameters.

[0048] In the above implementation method, For the target rotational speed with minimum speed protection, considering The sign of a positive or negative symbol is determined by comparison. The output value is obtained by comparing it with the minimum speed protection value. A preset reference speed threshold is used to prevent calculation distortion caused by low-speed measurement noise. Through an adaptive denominator, this formula ensures that the "relative speed deviation" maintains a reasonable numerical scale across the entire speed range of the vehicle, from standstill to high speed, giving the preset "activation threshold" consistent physical meaning and judgment validity under all operating conditions. Secondly, by introducing a preset reference speed threshold greater than zero for protection, miscalculations and false triggers that may occur in the low-speed range due to encoder noise or signal quantization errors are fundamentally eliminated, ensuring that the judgment of operating conditions remains stable and reliable during critical low-speed conditions such as vehicle start-up, creeping, or precise stopping.

[0049] Based on the aforementioned scheme, in some implementations of this application, the formula for calculating the feedforward torque is as follows: ; in, For feedforward torque, , This represents the current speed error. For the target speed, For feedback of rotational speed, For feedback torque, This is a first feedforward control system used to compensate for inertial drag during acceleration. This is the second feedforward control coefficient used to compensate for load variation trends. For preset protection items, , To output the maximum value among the comparison parameters, The preset reference speed threshold is greater than zero. This outputs the minimum value among the comparison parameters.

[0050] In the above implementation method, It is mainly related to the total mass of the vehicle and the inertia of the transmission system, and is used to compensate for inertial resistance during acceleration. This is related to the rolling resistance coefficient of the lawnmower on typical lawns (such as wet, slippery, and deep grass), and is used to compensate for load variation trends. Protection measures to prevent division by zero or noise amplification.

[0051] It should be noted that the above implementation method achieves this through separation. and Two independently calibrable coefficients enable feedforward compensation to precisely match the vehicle's inertial characteristics with the load characteristics under typical operating conditions, improving the targeting and accuracy of the compensation. Furthermore, its robust denominator design ( The design ensures that the feedforward output decays smoothly as it approaches steady state, avoiding continuous small oscillations and contributing to the stability of control.

[0052] Based on the aforementioned scheme, in some implementations of this application, the step of superimposing the calculated feedforward torque onto the output of the speed loop PID includes: multiplying the calculated feedforward torque by a weighted factor and then superimposing it onto the output of the speed loop PID; wherein, the weighted factor... The calculation formula is: ; , To measure the upper limit threshold of mode switching, To reach the minimum threshold for exiting the feedforward torque, This represents the relative velocity deviation.

[0053] In the above implementation, a soft transition and early unloading mechanism is designed by using a weighted sub-factor as a smoothing and attenuation control factor for the feedforward output, in order to avoid torque shocks caused by sudden output changes during the switching between feedforward and synchronous modes. Specifically, when... At this time, the feedforward torque is applied in full to ensure the strongest rapid compensation capability. When At this point, the feedforward torque decreases linearly from 1 to 0, achieving a smooth exit of the feedforward torque. This means that as the speed error gradually converges (e.g., the start-up process is nearing completion or the load disturbance is about to be overcome), the contribution of the feedforward torque also decreases smoothly. At this time, the feedforward torque is completely deactivated. Specifically, when the target speed command is detected to be about to stop (e.g., the user releases the accelerator) or entering zero-turn mode, the feedback speed decay process can be immediately initiated to unload the feedforward torque in advance, thus preventing the "push-back feeling" or "jerkiness" caused by mode switching. When a rapid convergence of speed error is detected, feedforward decay can be initiated in advance, reducing speed exponentially or linearly. To avoid sudden impact.

[0054] It should be noted that the formula for calculating the relative speed deviation can be the same as the formula mentioned above. You can use the absolute value for calculation, or you can use a formula. To perform the calculations. The target rotational speeds of the wheels corresponding to the left and right motors. This represents the actual rotational speed of the wheels corresponding to the left and right motors.

[0055] Based on the aforementioned solutions, such as Figure 2As shown, in some implementations of this application, the step of calculating the synchronization adjustment torque based on the target speed, feedback current, and feedback speed includes: Step S201: Calculating the synchronization error of the left and right motors based on the target speed and feedback speed; Step S202: Calculating the adaptive compensation gain of each of the left and right motors based on the feedback current; Step S203: Calculating the target adjustment speed of each of the left and right motors based on the operating mode of the left and right motors and the synchronization error and adaptive compensation gain, and determining the corresponding synchronization adjustment torque based on the target adjustment speed, wherein the operating mode of the left and right motors includes running in the same direction or running in opposite directions.

[0056] In the above implementation, the target speed and feedback speed of the left and right wheels are first compared to calculate the quantified synchronization error, which directly reflects the actual speed mismatch between the two wheels. Subsequently, the feedback current of the left and right motors is used to calculate their respective adaptive compensation gains in real time. The basic principle is that when the current (load) on one side increases, the compensation gain on the other side will increase, forming an intelligent adjustment trend of "the heavily loaded side is pulled, and the lightly loaded side actively cooperates".

[0057] In other words, the above implementation method, by introducing current-based adaptive gain, achieves dynamic and precise compensation for asymmetrical loads, fundamentally solving the problem of fixed-gain controller malfunction under conditions such as "single-sided grass pressing." Furthermore, by distinguishing between unidirectional and reverse operating modes, the synchronization strategy perfectly matches the vehicle's forward and turning requirements, ensuring both the accuracy of straight-line driving and the flexibility and smoothness of maneuvers such as turning on the spot.

[0058] Based on the aforementioned scheme, in some implementations of this application, the step of calculating the target adjustment speed of each of the left and right motors based on the operating modes of the left and right motors and the synchronization error and adaptive compensation gain includes: when the operating modes of the left and right motors are running in the same direction, the calculation formula for the target adjustment speed of each of the left and right motors is: ; When the left and right motors are running in opposite directions, the calculation formula for the target adjustment speed of each motor is as follows: ; .in, Adjust the speed for the target of the left motor. Adjust the speed for the target of the right motor. The target speed for the left motor. The target speed for the right motor. For the adaptive compensation gain of the left motor, The adaptive compensation gain for the right motor. This represents the synchronization error between the left and right motors.

[0059] In the above implementation method, running in the same direction ( During reverse operation, a deviation coupling strategy ensures high-precision speed proportional tracking, guaranteeing the straightness of the driving trajectory. When switching to a uniform attenuation strategy, the speed and smoothness of differential establishment are ensured, significantly improving steering handling quality and vehicle stability. This allows the vehicle to achieve optimal synchronization performance whether operating in a straight line or navigating agilely.

[0060] For example, in some implementations of this application, when... and When inputting to the speed PID controller to adjust the synchronous adjustment torque, anti-saturation measures can be adopted to prevent PID integral saturation from causing response lag: when the PID output reaches the upper or lower limit and the error has the same sign as the output, the integral accumulation is paused. When the error reverses, the integral term is allowed to be released quickly, improving the system's recovery speed after large disturbances. This, combined with feedforward, forms a collaborative mechanism of "feedforward main control + feedback fine-tuning".

[0061] In some implementations of this application, to prevent miscompensation caused by measurement noise, encoder resolution limitations, or motor control dead zones under low-speed or minor disturbance conditions, [the following measures are taken]. A synchronization error dead zone is set. That is, if Then let ,in, This is the error dead zone threshold.

[0062] For example, in the above implementation, The calculation formula can be: .in, The desired speed ratio calculated based on the target speed. This represents the rotational speed of the wheel corresponding to the left motor. This represents the rotational speed of the wheel corresponding to the right motor. .

[0063] and The calculation formulas are as follows:

[0064]

[0065] in, The baseline compensation coefficient is greater than zero. This is the load weighting factor for the left motor, used for calculating the compensation gain of the left motor. Its value increases as the load on the right motor increases. This is the load weighting factor for the right motor, used for calculating the compensation gain of the right motor. Its value increases as the load on the left motor increases.

[0066] and The formula for calculation is:

[0067] in, , This is the absolute value of the feedback current of the left motor. This is the absolute value of the feedback current of the right motor.

[0068] Based on the aforementioned solutions, such as Figure 3 As shown, in some implementations of this application, after obtaining the final output torque that drives the left and right motors to operate, the method further includes step S105: performing nonlinear speed limiting processing on the final output torque, and outputting the processed torque output command to the current loop of the corresponding motor.

[0069] In the above implementation, nonlinear speed limiting is introduced to prevent the motor from running at overspeed, thereby smoothly attenuating the torque output in the overspeed direction, avoiding mechanical impact, and ensuring system safety.

[0070] For example, the calculation formula for this nonlinear velocity limiting process can be:

[0071] in, The attenuation coefficient is greater than zero. To achieve the final output torque after nonlinear speed limiting processing, For feedforward torque, The preset maximum allowable speed for the left and right motors. The actual speed of the left and right motors (its value can be...) (To reflect).

[0072] Exemplary electric vehicle Please see Figure 4 This application provides an electric vehicle, which includes at least one processor 201 and at least one memory 202. The processor 201 and memory 202 are directly connected to each other, or communicate with each other through a communication interface 203, or are electrically connected through one or more communication buses or signal lines to achieve data transmission or interaction. The memory 202 stores program instructions executable by the processor 201, which can call and execute the program instructions to implement a drive control method for an electric vehicle according to various embodiments of this application as described in the "Exemplary Methods" section above. For example, implementing: The system acquires the target speed, feedback current, feedback speed, and feedback torque of the left and right motors. Based on the target speed and feedback speed, it determines the operating condition of the electric vehicle and obtains the current operating condition information. When the current operating condition information indicates that the electric vehicle is in the first operating condition, if the feedforward start condition is not met, the feedforward torque is set to zero. If the feedforward start condition is met, the feedforward torque is calculated based on the target speed, feedback speed, and feedback torque, and the calculated feedforward torque is superimposed on the output of the speed loop PID as an additional input to the current loop. When the current operating condition information indicates that the electric vehicle is in the second operating condition, the synchronization adjustment torque is calculated based on the target speed, feedback current, and feedback speed to obtain the synchronization adjustment torque. The synchronization adjustment torque is then fused with the feedforward torque calculated under the previous first operating condition to obtain the final output torque that drives the left and right motors.

[0073] The memory 202 may be, but is not limited to, random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), etc.

[0074] The processor 201 can be an integrated circuit chip with signal processing capabilities. The processor 201 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0075] Understandable. Figure 4 The structure shown is for illustrative purposes only; electric vehicles may also include structures that are more advanced than those shown. Figure 4 The more or fewer components shown, or having the same Figure 4 The different configurations shown. Figure 4The components shown can be implemented using hardware, software, or a combination thereof.

[0076] Exemplary computer-readable storage medium and computer program product This application provides a computer-readable storage medium having a computer program stored thereon. When executed by a processor 201, the computer program implements a drive control method for an electric vehicle according to various embodiments of this application as described in the "Exemplary Methods" section above. For example, it implements: The system acquires the target speed, feedback current, feedback speed, and feedback torque of the left and right motors. Based on the target speed and feedback speed, it determines the operating condition of the electric vehicle and obtains the current operating condition information. When the current operating condition information indicates that the electric vehicle is in the first operating condition, if the feedforward start condition is not met, the feedforward torque is set to zero. If the feedforward start condition is met, the feedforward torque is calculated based on the target speed, feedback speed, and feedback torque, and the calculated feedforward torque is superimposed on the output of the speed loop PID as an additional input to the current loop. When the current operating condition information indicates that the electric vehicle is in the second operating condition, the synchronization adjustment torque is calculated based on the target speed, feedback current, and feedback speed to obtain the synchronization adjustment torque. The synchronization adjustment torque is then fused with the feedforward torque calculated under the previous first operating condition to obtain the final output torque that drives the left and right motors.

[0077] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may, for example, include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0078] Furthermore, embodiments of this application can also be computer program products, including computer program instructions that, when executed by a processor, implement the steps of a drive control method for an electric vehicle according to various embodiments of this application as described in the "Exemplary Methods" section above. For example, implementing: The system acquires the target speed, feedback current, feedback speed, and feedback torque of the left and right motors. Based on the target speed and feedback speed, it determines the operating condition of the electric vehicle and obtains the current operating condition information. When the current operating condition information indicates that the electric vehicle is in the first operating condition, if the feedforward start condition is not met, the feedforward torque is set to zero. If the feedforward start condition is met, the feedforward torque is calculated based on the target speed, feedback speed, and feedback torque, and the calculated feedforward torque is superimposed on the output of the speed loop PID as an additional input to the current loop. When the current operating condition information indicates that the electric vehicle is in the second operating condition, the synchronization adjustment torque is calculated based on the target speed, feedback current, and feedback speed to obtain the synchronization adjustment torque. The synchronization adjustment torque is then fused with the feedforward torque calculated under the previous first operating condition to obtain the final output torque that drives the left and right motors.

[0079] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this application. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0080] It will be apparent to those skilled in the art that this application is not limited to the details of the exemplary embodiments described above, and that this application can be implemented in other specific forms without departing from the spirit or essential characteristics of this application. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of this application is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within this application. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A drive control method for an electric vehicle, characterized in that, The left and right drive wheels of the electric vehicle are driven independently by left and right motors. The method includes the following steps: Obtain the target speed, feedback current, feedback speed, and feedback torque of the left and right motors; Based on the target speed and the feedback speed, the operating condition of the electric vehicle is determined, and the current operating condition information is obtained. When the current operating condition information indicates that the electric vehicle is in the first operating condition, if the feedforward start condition is not met, the feedforward torque is set to zero. If the feedforward start condition is met, the feedforward torque is calculated based on the target speed, feedback speed and feedback torque, and the calculated feedforward torque is superimposed on the output of the speed loop PID as an additional input to the current loop. When the current operating condition information indicates that the electric vehicle is in the second operating condition, the synchronous adjustment torque is calculated based on the target speed, feedback current and feedback speed to obtain the synchronous adjustment torque. The synchronous adjustment torque is then fused with the feedforward torque calculated under the previous first operating condition to obtain the final output torque that drives the left and right motors.

2. The method according to claim 1, characterized in that, The step of determining the operating conditions of the electric vehicle based on the target speed and the feedback speed includes: The relative speed deviation between the target speed and the feedback speed is calculated, and the operating condition of the electric vehicle is determined based on the comparison between the relative speed deviation and a preset activation threshold. If the absolute value of the relative speed deviation is greater than the preset activation threshold, the operating condition of the electric vehicle is determined to be the first operating condition; otherwise, the operating condition of the electric vehicle is determined to be the second operating condition.

3. The method according to claim 2, characterized in that, The formula for calculating the relative velocity deviation is: ; in, , For relative speed deviation, For the target speed, For feedback of rotational speed, The preset reference speed threshold is greater than zero. To output the maximum value among the comparison parameters, This outputs the minimum value among the comparison parameters.

4. The method according to claim 1, characterized in that, The feedforward start condition is that the target rotational speed and the feedback rotational speed are in the same direction.

5. The method according to claim 1, characterized in that, The formula for calculating the feedforward torque is: ; in, For feedforward torque, , This represents the current speed error. For the target speed, For feedback of rotational speed, For feedback torque, This is a first feedforward control system used to compensate for inertial drag during acceleration. This is the second feedforward control coefficient used to compensate for load variation trends. For preset protection items, , To output the maximum value among the comparison parameters, The preset reference speed threshold is greater than zero. This outputs the minimum value among the comparison parameters.

6. The method according to claim 5, characterized in that, The step of superimposing the calculated feedforward torque onto the output of the velocity loop PID includes: multiplying the calculated feedforward torque by a weighted factor and then superimposing it onto the output of the velocity loop PID; wherein, the weighted factor The calculation formula is: ; , To measure the upper limit threshold of mode switching, To reach the minimum threshold for exiting the feedforward torque, This represents the relative velocity deviation.

7. The method according to claim 1, characterized in that, The step of calculating the synchronous adjustment torque based on the target speed, feedback current, and feedback speed includes: The synchronization error of the left and right motors is calculated based on the target speed and the feedback speed. Calculate the adaptive compensation gain of the left and right motors based on the feedback current; Based on the operating modes of the left and right motors and the synchronization error and adaptive compensation gain, the target adjustment speed of each of the left and right motors is calculated, and the corresponding synchronization adjustment torque is determined according to the target adjustment speed. The operating modes of the left and right motors include running in the same direction or running in opposite directions.

8. The method according to claim 7, characterized in that, The step of calculating the target adjustment speed of each of the left and right motors based on the operating modes of the left and right motors, the synchronization error, and the adaptive compensation gain includes: When the left and right motors are operating in the same direction, the calculation formula for the target adjustment speed of each motor is as follows: ; ; When the left and right motors are running in opposite directions, the calculation formula for the target adjustment speed of each motor is as follows: ; ; in, Adjust the speed for the target of the left motor. Adjust the speed for the target of the right motor. The target speed for the left motor. The target speed for the right motor. For the adaptive compensation gain of the left motor, The adaptive compensation gain for the right motor. This represents the synchronization error between the left and right motors.

9. The method according to claim 1, characterized in that, After obtaining the final output torque that drives the left and right motors, the method further includes: performing nonlinear speed limiting processing on the final output torque, and outputting the processed torque output command to the current loop of the corresponding motor.

10. An electric vehicle, characterized in that, The left and right drive wheels of the electric vehicle are driven independently by left and right motors, and the electric vehicle also includes: Memory, used to store one or more programs; processor; When the one or more programs are executed by the processor, the method as described in any one of claims 1-9 is implemented.

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