Drive control method for an electric drive system and related device

Abstract

The application relates to the technical field of electric drive systems, in particular to a drive control method of an electric drive system and related equipment, wherein the method comprises the following steps: obtaining driving input instructions, vehicle parameters and a battery state of charge at a current time step; determining a required power according to the driving input instructions and the vehicle parameters; determining fuel output power and battery output power according to the battery state of charge and the required power; determining total drive torque and an additional yaw moment according to the sum of the fuel output power and the battery output power; determining expected drive torques of a plurality of drive motors according to the total drive torque and the additional yaw moment; and generating drive instructions according to the expected drive torques. When the remaining capacity of the battery is large, the battery output power is increased and the fuel output power is reduced according to the battery state of charge and the required power, so that optimal power distribution of an engine and a motor can be realized, fuel economy is improved, yaw stability control and independent control of the drive motors are realized.

Description

Technical Field

[0001] This application relates to the field of electric drive system technology, and in particular to drive control methods and related equipment for electric drive systems. Background Technology

[0002] Among related technologies, there is a distributed drive technology for vehicles. This involves using a model predictive trajectory control algorithm to calculate the total driving force and total yaw moment in the current control cycle, and then using a multi-objective optimization algorithm to calculate the torque required by the drive motors of each wheel. In special engineering scenarios, the electric drive system of engineering vehicles typically adopts a hybrid power supply scheme of power batteries and generators to meet the power requirements under operating conditions. The electric drive system of engineering vehicles switches the operating modes of the engine and motor based on fixed threshold rules, and independently controls torque distribution through a torque controller and yaw suppression through a yaw controller. However, this approach lacks coordination between several control links, making it difficult to achieve fuel economy and yaw stability control when independently controlling the torque of each drive motor in special engineering scenarios. Summary of the Invention

[0003] In view of this, embodiments of this application propose a drive control method and related equipment for an electric drive system, which can improve fuel economy and achieve yaw stability control and independent control of the drive motor.

[0004] To achieve the above objectives, one aspect of this application proposes a drive control method for an electric drive system, the method comprising the following steps: Obtain the driving input commands, vehicle parameters, and battery charge status at the current time step; The required power is determined based on the driving input command and the vehicle parameters, and the fuel output power and battery output power are determined based on the battery state of charge and the required power, wherein the battery state of charge and battery output power are positively correlated. The total drive torque and additional yaw torque are determined based on the sum of the fuel output power and the battery output power; the desired drive torque of several drive motors is determined based on the total drive torque and the additional yaw torque; and drive commands are generated based on the desired drive torque.

[0005] In some embodiments, determining the fuel output power and battery output power based on the battery state of charge and the required power includes: The battery state of charge is input into a pre-built PI controller, and an equivalent factor is determined by the PI controller. The PI controller is configured to perform proportional-integral calculation based on the deviation between the battery state of charge and a reference value. When the battery state of charge is lower than the reference value, the equivalent factor is decreased, and when the battery state of charge is higher than the reference value, the equivalent factor is increased. A first objective function for power distribution calculation is determined based on the equivalent factor, and the first objective function is solved to obtain the fuel output power and the battery output power.

[0006] In some embodiments, the first objective function is determined through the following steps: Construct a first objective function with the goal of minimizing fuel consumption. The first objective function is obtained by adding a first component and a second component. The first component represents the actual fuel consumption of the generator, and the second component represents the equivalent fuel consumption of the battery output power. Determine the constraints of the first objective function.

[0007] In some embodiments, determining the total drive torque and additional yaw moment based on the sum of the fuel output power and the battery output power includes: The total drive torque is obtained by calculating the sum of the fuel output power and the battery output power; The total driving torque is input into the pre-built trajectory tracking controller, which outputs the hinge angle command. The hinge angle command is input into a pre-built linear quadratic regulator, which outputs the additional yaw moment. The trajectory tracking controller is configured to be based on an articulated vehicle kinematics model, with the goal of minimizing lateral position error and heading angle error, and to obtain the articulation angle command by solving a model predictive control algorithm. The linear quadratic regulator is configured to calculate the desired yaw rate according to the articulation angle command, and to calculate the additional yaw moment by solving the optimal feedback gain matrix, using the center of mass sideslip angle and the state error of the yaw rate as inputs.

[0008] In some embodiments, determining the desired drive torque of a plurality of drive motors based on the total drive torque and the additional yaw moment includes: The total drive torque and the additional yaw moment are input into a pre-constructed quadratic programming controller, which outputs the desired drive torque of several drive motors. The quadratic programming controller is configured to obtain the desired drive torque of several drive motors by solving a second objective function based on minimizing the driving force tracking error, minimizing the yaw moment tracking error, minimizing the tire utilization variance, and minimizing the overall motor loss.

[0009] In some embodiments, generating drive commands based on the desired drive torque includes: The current road surface type and optimal slip ratio are estimated using a fuzzy observer; The desired driving torque is input into a pre-built sliding mode controller, which outputs a driving command. The sliding mode controller is configured to reduce the driving torque of the current wheel to bring the wheel slip ratio back to the optimal slip ratio when the wheel slip ratio exceeds a threshold.

[0010] To achieve the above objectives, another aspect of this application provides a drive control device for an electric drive system, the device comprising: The acquisition module is used to acquire the driving input commands, vehicle parameters, and battery charge status at the current time step; The power distribution module is used to determine the required power based on the driving input command and the vehicle parameters, and to determine the fuel output power and battery output power based on the battery state of charge and the required power, wherein the battery state of charge and battery output power are positively correlated. The torque distribution module is used to determine the total drive torque and the additional yaw torque based on the sum of the fuel output power and the battery output power; determine the desired drive torque of several drive motors based on the total drive torque and the additional yaw torque; and generate drive commands based on the desired drive torque.

[0011] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the methods described above.

[0012] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods described above.

[0013] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer program product, including a computer program that, when executed by a processor, implements the methods described above.

[0014] To achieve the above objectives, another aspect of this application provides an electric drive system, the electric drive system comprising: Sensors are used to collect driving input commands, vehicle parameters, and battery state of charge; A controller configured to perform the steps described above; A drive motor is communicatively connected to the controller, and the drive motor is used to generate torque according to the torque command output by the controller; The power supply unit is communicatively connected to the controller and is equipped with a generator and a power battery. The power supply unit is used to control the generator and the power battery to output power to the drive motor according to the power distribution command sent by the controller.

[0015] To achieve the above objectives, another aspect of the embodiments of this application proposes an engineering vehicle, which includes a front vehicle body, a rear vehicle body, and the electric drive system described above, wherein the front vehicle body and the rear vehicle body are hinged together.

[0016] The embodiments of this application include at least the following beneficial effects: This application provides a drive control method and related equipment for an electric drive system. This scheme obtains the driving input command, vehicle parameters, and battery state of charge at the current time step. Based on the driving input command and vehicle parameters, it determines the required power. Based on the battery state of charge and the required power, it determines the fuel output power and battery output power, wherein the battery state of charge and battery output power are positively correlated. Based on the sum of the fuel output power and battery output power, it determines the total drive torque and the additional yaw moment. Based on the total drive torque and the additional yaw moment, it determines the desired drive torque of several drive motors and generates a drive command based on the desired drive torque. When the remaining battery capacity is large, the battery output power is increased and the fuel output power is reduced based on the battery state of charge and the required power, thus achieving optimal power distribution between the engine and motors, which is beneficial for improving fuel economy. Furthermore, this scheme determines the desired drive torque of several drive motors based on the total drive torque and the additional yaw moment, and independently distributes torque to multiple drive motors using the desired drive torque, generating an additional yaw moment to control the vehicle's yaw stability. Attached Figure Description

[0017] Figure 1 This is a flowchart of the drive control method for the electric drive system provided in the embodiments of this application; Figure 2 This is a flowchart of the steps for determining fuel output power and battery output power in the method provided in the embodiments of this application; Figure 3 This is a flowchart illustrating the method for determining the total driving torque and the additional yaw moment provided in the embodiments of this application; Figure 4 This is a schematic diagram of the control architecture of the drive control method for the electric drive system provided in the embodiments of this application; Figure 5 This is a schematic diagram of the drive control device of the electric drive system provided in the embodiments of this application; Figure 6 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0019] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various concepts, but unless otherwise stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words “if,” “when,” or “in response to a determination” as used herein may be interpreted as “when…” or “when…” or “in response to a determination.”

[0020] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0022] Before providing a detailed description of the embodiments of this application, some of the nouns and terms involved in the embodiments of this application will be explained first. The nouns and terms involved in the embodiments of this application are subject to the following interpretations.

[0023] A distributed electric drive system is a drive axle architecture in which the motor is placed inside or near the wheels, and each wheel is driven by an independent motor.

[0024] Among related technologies, there is a distributed drive technology for vehicles. This involves using a model predictive trajectory control algorithm to calculate the total driving force and total yaw moment in the current control cycle, and then using a multi-objective optimization algorithm to calculate the torque required by the drive motors of each wheel. In special engineering scenarios, the electric drive system of engineering vehicles typically adopts a hybrid power supply scheme of power batteries and generators to meet the power requirements under operating conditions. The electric drive system of engineering vehicles switches the operating modes of the engine and motor based on fixed threshold rules, and independently controls torque distribution through a torque controller and yaw suppression through a yaw controller. However, this approach lacks coordination between several control links, making it difficult to achieve fuel economy and yaw stability control when independently controlling the torque of each drive motor in special engineering scenarios.

[0025] In addition, the front and rear sections of the articulated dump truck are connected by an articulated structure, which can cause folding and tail-swing when the driving torque generated by each wheel is unbalanced.

[0026] In view of this, this application provides a drive control method and related equipment for an electric drive system. This method determines the required power based on the driving input command and the vehicle parameters, determines the fuel output power and battery output power based on the battery state of charge and the required power, determines the total drive torque and additional yaw moment based on the sum of the fuel output power and the battery output power, determines the desired drive torque of several drive motors based on the total drive torque and the additional yaw moment, and generates drive commands based on the desired drive torque. This method can organically integrate multiple control objectives such as minimizing fuel consumption, controlling yaw stability, and coordinating torque distribution, and is suitable for special engineering vehicles, especially articulated dump trucks.

[0027] The drive control method for an electric drive system provided in this application relates to the field of electric drive system technology. This drive control method can be applied to a vehicle controller, an edge controller, or software running on an onboard computing platform or terminal. The vehicle controller or edge controller can be configured as a vehicle controller, power domain controller, chassis domain controller, distributed drive motor controller, or electronic control unit, etc. These controllers can be configured as independent physical control modules, or as a domain controller or central computing platform composed of multiple integrated control modules, or as an onboard computing node providing real-time calculation, data fusion, and control algorithm execution. The software can be an application program or underlying firmware that implements the drive control method for the electric drive system, but is not limited to the above forms.

[0028] This application can be used in numerous general-purpose or special-purpose computer system environments or configurations. Examples include: vehicle controllers, distributed drive motor controllers, electronic control units, domain controllers, in-vehicle computing platforms, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via in-vehicle communication networks (such as CAN bus, in-vehicle Ethernet, etc.) or external communication networks. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0029] Figure 1 This is an optional flowchart of the drive control method for the electric drive system provided in the embodiments of this application. Figure 1 The method may include, but is not limited to, steps 101 to 103.

[0030] Step 101: Obtain the driving input commands, vehicle parameters, and battery charge status at the current time step; In step 101, driving input commands include accelerator pedal travel and steering wheel angle, etc. Vehicle parameters include vehicle longitudinal speed, acceleration, wheel speed, sideslip angle, etc., collected by sensors or predicted by a state observer. Battery state of charge is used to indicate the remaining charge at the current time step.

[0031] Step 102: Determine the required power based on the driving input command and the vehicle parameters, and determine the fuel output power and battery output power based on the battery state of charge and the required power, wherein the battery state of charge and battery output power are positively correlated; In step 102, the required power determines the total longitudinal force the vehicle needs to output. By observing the battery's state of charge, the power output shared by the generator and the battery is adjusted. For example, in the current time step, the fuel output power equals 40% of the required power, while the battery output power equals 60% of the required power. When the battery's state of charge is high, the system automatically adjusts to increase the battery output power, thereby reducing the fuel output power and lowering fuel consumption.

[0032] Step 103: Determine the total drive torque and additional yaw torque based on the sum of the fuel output power and the battery output power; determine the desired drive torque of several drive motors based on the total drive torque and the additional yaw torque; and generate drive commands based on the desired drive torque.

[0033] In step 103, the additional yaw moment is used to balance the vehicle's lateral moment to maintain balance. The total drive torque is determined by calculating the sum of the fuel output power and the battery output power. Since torque imbalance among the distributed drive motors causes lateral swaying of the vehicle, the additional yaw moment needs to be calculated. The distributed drive motors are then controlled to generate this additional yaw moment to counteract the lateral yaw moment. The final output is the independent desired drive torque for each drive motor, which, when executed by each drive motor, generates the total drive torque and the additional yaw moment.

[0034] Steps 101 to 103 of this embodiment involve acquiring the driving input command, vehicle parameters, and battery state of charge (SBC) at the current time step. The required power is determined based on the driving input command and vehicle parameters. The fuel output power and battery output power are determined based on the battery SBC and the required power, wherein the battery SBC and battery output power are positively correlated. The total drive torque and additional yaw torque are determined based on the sum of the fuel output power and battery output power. The desired drive torque of several drive motors is determined based on the total drive torque and the additional yaw torque. Drive commands are generated based on the desired drive torque. When the remaining battery capacity is large, the battery output power is increased and the fuel output power is decreased based on the battery SBC and the required power, thus achieving optimal power distribution between the engine and motors and improving fuel economy. Furthermore, this solution determines the desired drive torque of several drive motors based on the total drive torque and the additional yaw torque, and independently distributes torque to multiple drive motors using the desired drive torque to generate an additional yaw torque to control the vehicle's yaw stability.

[0035] See Figure 2 In some embodiments, determining the fuel output power and battery output power based on the battery state of charge and the required power includes: Step 201: Input the battery state of charge into a pre-built PI controller, and determine the equivalent factor through the PI controller. The PI controller is configured to perform proportional-integral calculation based on the deviation between the battery state of charge and the reference value. When the battery state of charge is lower than the reference value, the equivalent factor is decreased, and when the battery state of charge is higher than the reference value, the equivalent factor is increased. For example, the equivalent factor The calculation formula is: ; in, This is the initial equivalence factor; For reference only; For proportional gain; For integral gain, The battery is in its state of charge. It is an equivalent factor.

[0036] When the SOC is lower than the reference value, the equivalent factor automatically decreases (the strategy tends to use more fuel and less electricity to protect the battery); when the SOC is higher than the reference value, the equivalent factor increases (the strategy tends to use more electricity and less fuel).

[0037] Step 202: Determine the first objective function for power distribution calculation based on the equivalent factor, solve the first objective function, and obtain the fuel output power and the battery output power.

[0038] In some specific embodiments of step 202, the first objective function is determined through the following steps: Step 2021: Construct the first objective function with the optimization objective of minimizing fuel consumption. The first objective function is obtained by adding a first component and a second component. The first component is used to represent the actual fuel consumption of the generator, and the second component is used to represent the equivalent fuel consumption of the battery output power. Step 2022: Determine the constraints of the first objective function.

[0039] In steps 2021 and 2022, in each control cycle, the following constrained first objective function is solved: , , The constraints are: , , ; in, fuel output power Fuel consumption below This refers to the equivalent fuel consumption of the power battery. As an equivalent factor, For fuel output power, For the required power, For fuel output power, At minimum battery state of charge, At maximum battery state of charge, This refers to the battery's output power. It is a fuel with a low calorific value; This refers to the engine speed.

[0040] By performing discrete sampling and evaluating the first objective function within the engine torque range (one-dimensional search method) in real time, the computational complexity is low, with a single-step calculation time of approximately 25ms, which meets the real-time requirements.

[0041] In this embodiment, when the required power When the power demand is less than the motor's maximum output power and the State of Charge (SOC) is higher than the minimum threshold, the engine shuts off, and the battery powers the system alone, achieving zero-emission operation. This is suitable for emission-sensitive scenarios such as vehicle start-up, low-speed on-site operations, enclosed construction sites, and tunnels. When the power demand exceeds the power corresponding to the engine's optimal output torque, the engine and motor work together to drive the vehicle. The engine operates within its optimal fuel consumption range, providing the basic power, while the motor dynamically compensates for peak power demand, achieving hybrid-electric synergy. When the SOC is lower than the safety threshold... During normal operation, the engine directly provides the power required by the vehicle and simultaneously drives the generator to charge the battery, gradually restoring the State of Charge (SOC) to its normal range. Under heavy loads, downhill driving, or braking conditions, the electric motor performs regenerative braking to recover kinetic energy, while the engine drives the generator at a constant, efficient speed to charge the battery, maximizing energy recovery efficiency. The above mode switching is determined based on an equivalent factor, and the switching process is smooth and seamless.

[0042] See Figure 3 In some embodiments, determining the total drive torque and additional yaw moment based on the sum of the fuel output power and the battery output power includes: Step 301: Calculate the sum of the fuel output power and the battery output power to obtain the total drive torque; Step 302: Input the total driving torque into the pre-built trajectory tracking controller and output the articulation angle command; wherein, the trajectory tracking controller is configured to be based on the articulated vehicle kinematics model, with the goal of minimizing the lateral position error and heading angle error, and the articulation angle command is obtained by solving the model predictive control algorithm; In step 302, the control objective of the trajectory tracking controller is to minimize the lateral position error. and heading angle error The mathematical representation of the trajectory tracking controller is: ; in, For prediction in the time domain; To control the time domain; Weighting for heading angle error; To control incremental weights; This refers to the lateral position error; The heading angle error is represented by the value; this quadratic programming problem is solved within each control cycle (10ms).

[0043] Step 303: Input the hinge angle command into the pre-built linear quadratic regulator and output the additional yaw moment; The linear quadratic regulator is configured to calculate the desired yaw rate based on the hinge angle command, and to calculate the additional yaw torque by solving the optimal feedback gain matrix, using the centroid sideslip angle and the state error of the yaw rate as inputs.

[0044] In step 303, the construction process of the linear quadratic regulator is as follows: First, a linear two-degree-of-freedom vehicle reference model is established, and the desired yaw rate is calculated. : , in, For insufficient steering gradient; The hinge angle; For the desired yaw rate, This is the distance from the center of mass to the front axle; This is the distance from the center of mass to the rear axle; This is the equivalent lateral stiffness of the rear axle; This is the equivalent lateral stiffness of the front axle; For the overall vehicle weight; This refers to the vehicle's longitudinal speed.

[0045] Define state error: , in, The sideslip angle is the angle of the center of mass. To determine the desired centroid sideslip angle, This is the actual yaw rate. Let be the desired yaw rate.

[0046] The performance metrics are defined as follows: .

[0047] in, The control weighting factor for the additional yaw moment, The weight matrix for the state error is used. The optimal feedback gain matrix G is obtained by solving the Riccati equation, with an additional yaw moment. The LQR weight matrix was tuned offline using a hybrid genetic algorithm-particle swarm optimization algorithm. This is the feedback gain for the centroid sideslip angle error. This is the error in the centroid sideslip angle. The feedback gain for the yaw rate error. This represents the yaw rate error.

[0048] In this embodiment, in response to the instability issues such as folding and fishtailing that can easily occur when the front and rear bodies of an articulated vehicle rotate relative to each other around the articulation point during steering, the trajectory tracking controller and the linear quadratic regulator generate additional yaw torque by differentially driving each drive motor, thereby stabilizing the vehicle's yaw motion.

[0049] In some embodiments, determining the desired drive torque of a plurality of drive motors based on the total drive torque and the additional yaw moment includes: The total driving torque and the additional yaw moment are input into a pre-constructed quadratic programming controller, which outputs the desired driving torque of several driving motors. The quadratic programming controller is configured to solve a second objective function based on minimizing the driving force tracking error, minimizing the yaw moment tracking error, minimizing the tire utilization variance, and minimizing the overall motor loss to obtain the desired driving torque of several driving motors.

[0050] For example, the second objective function is: ; The first objective is to minimize the tracking error of the total driving force of the six wheels to the target driving force; the second objective is to minimize the tracking error of the actual additional yaw moment to the commanded yaw moment; the third objective is to minimize the variance of the utilization rate of the six tires to ensure balanced load on each wheel; and the fourth objective is to minimize the overall working loss of the six hub motors. , , The weighting coefficients for each item are determined through offline calibration; Let be the driving torque of the i-th wheel, i=1,2,…,6; The radius of the wheel's rolling radius; Let be the lateral distance from the i-th wheel to the vehicle's center of mass; The overall driving force for the goal; The road surface adhesion coefficient; Let be the vertical load on the i-th wheel; Let be the operating loss of the i-th hub motor under the corresponding driving torque.

[0051] The constraints include: ; .

[0052] in, This represents the motor torque limit; Let be the driving torque of the i-th wheel. The road surface adhesion coefficient, Let be the vertical load on the i-th wheel. Let be the rotational speed of the i-th motor.

[0053] In this embodiment, when obtaining the total driving torque and additional yaw moment Subsequently, the six-wheel torque distribution problem is transformed into a constrained quadratic programming optimization problem. A simplified analytical method is used to solve the second objective function. Under the premise of meeting the additional yaw moment requirements, the torque is preferentially distributed to the wheels with larger vertical loads and higher motor efficiency, which can improve yaw stability.

[0054] In some embodiments, generating drive commands based on the desired drive torque includes: The current road surface type and optimal slip ratio are estimated using a fuzzy observer. The desired driving torque is input into a pre-built sliding mode controller, which outputs a driving command. The sliding mode controller is configured to reduce the driving torque of the current wheel to bring the wheel slip ratio back to the optimal slip ratio when the wheel slip ratio exceeds a threshold.

[0055] For example, the road adhesion coefficient is described using the Burckhardt tire model. With slip ratio Relationship: Thus, the optimal slip ratio is determined. for: ,in, The peak adhesion coefficient of the road surface. This is the adhesion curve shape factor. The curvature coefficient of the adhesion curve. , , All parameters are Burckhardt tire model fitting parameters determined by road surface type and can be determined by looking up a table based on road surface type.

[0056] In this embodiment, when the slip ratio of a certain wheel exceeds a threshold When the slip ratio returns to its optimal value, the anti-slip controller intervenes, reducing the drive torque of that wheel and suppressing yaw disturbances through asymmetric torque distribution, thus maintaining the vehicle's straight-line stability.

[0057] The following section provides a detailed description and explanation of the embodiments of the present invention, using a specific example of a six-wheel distributed motor drive system for a hybrid articulated dump truck: This application provides a six-wheel distributed motor drive control method for a hybrid articulated dump truck. It adopts a parallel hybrid architecture, and the power system consists of a diesel engine and six independent wheel hub motors. The vehicle adopts a "front axle dual-wheel + middle axle dual-wheel + rear axle dual-wheel" layout, with each wheel independently driven by a built-in permanent magnet synchronous wheel hub motor. The control strategy adopts a three-layer hierarchical control architecture of "decision-coordination-execution", and the layers interact with each other through a standard CAN bus interface.

[0058] See Figure 4 The upper control layer is the decision-making layer, responsible for vehicle-level energy management and MPC trajectory tracking; the middle control layer is the coordination layer, responsible for LQR yaw stability control and six-wheel QP torque coordination distribution; the lower control layer is the execution layer, responsible for SMC drive anti-slip control and motor torque execution.

[0059] In the upper-level control, an adaptive equivalent fuel consumption minimization strategy is employed to manage energy between the power battery and the diesel engine. Trajectory tracking uses a model predictive control (MPC) framework, which predicts future states based on an articulated vehicle kinematics model and optimizes the articulation angle control commands.

[0060] Specifically, energy management employs an adaptive equivalent fuel consumption minimization strategy. Based on the Pontryagin minimum principle, it introduces an equivalent factor *s* to equate electrical energy consumption to fuel consumption, transforming the global optimization problem into a real-time solvable instantaneous optimization problem. The equivalent factor is adjusted in real-time by a proportional-integral (PI) controller based on battery state of charge (SOC) feedback. For example, the mathematical representation of the proportional-integral (PI) controller is as follows: , in, As the initial equivalent factor, This is the SOC reference value. For proportional gain, This is the integral gain. When the State of Charge (SOC) is lower than the reference value, the equivalent factor automatically decreases, and the strategy tends to use more fuel; when the SOC is higher than the reference value, the equivalent factor increases, and the strategy tends to use more electrical energy.

[0061] In each control cycle, solve the following first objective function: , The constraints are: , , ; in, To optimize the objective, fuel output power Fuel consumption below This refers to the equivalent fuel consumption of the power battery. As an equivalent factor, For fuel output power, For the required power, For fuel output power, At minimum battery state of charge, At maximum battery state of charge, This refers to the battery's output power.

[0062] This optimization problem employs a one-dimensional search method to discretely sample and evaluate the objective function within the engine torque range, solving it in real time with a single-step computation time of approximately 25ms. Based on the optimization results, the system automatically switches between pure electric mode, hybrid mode, pure engine mode, and driving-charging mode.

[0063] The trajectory tracking in the upper-level control employs a model predictive control (MPC) framework. Based on the kinematic model of the articulated vehicle, it predicts the future state and optimizes the articulation angle control command. The control objective is to minimize the lateral position error and heading angle error. The prediction is performed in the time domain. , Control time domain .

[0064] In the mid-level control, the LQR yaw stability control uses the sideslip angle β and yaw rate γ as control variables, and designs an additional yaw moment controller based on the optimal control theory of the linear quadratic regulator (LQR). First, a linear two-degree-of-freedom vehicle reference model is established, and the desired yaw rate is calculated. ,in, For insufficient turning gradient, This is the hinge angle. State error. definition: LQR performance metrics: The optimal feedback gain matrix G is obtained by solving the Riccati equation. Finally, the additional yaw moment is calculated. for: The LQR weight matrix was tuned offline using a hybrid optimization algorithm combining genetic algorithm and particle swarm optimization.

[0065] The six-wheel torque distribution in the mid-level control adopts the quadratic programming (QP) method to obtain the total drive torque. and additional yaw moment Then, the torque distribution problem is transformed into a constrained optimization problem (the second objective function).

[0066] The second objective function consists of four weighted composite indices: minimizing the driving force tracking error, minimizing the yaw moment tracking error, minimizing the tire utilization variance, and minimizing the overall motor losses. Constraints include motor torque limit constraints. and tire adhesion limit constraints .

[0067] The lower-level control is the execution layer, responsible for SMC drive anti-slip control and motor torque execution. The anti-slip control uses a sliding mode control (SMC) algorithm, defining the slip ratio error as follows: Sliding surface: The control law is: ,in, For sliding mode gain, To determine the boundary layer thickness, a saturation function `sat` is used instead of the sign function to suppress chattering, and the integral term eliminates steady-state errors. The system uses a Burckhardt tire model and real-time measured wheel speed and vehicle speed signals, employing a fuzzy observer to estimate the current road surface type and optimal slip ratio. The road surface recognition response time is less than 0.5 seconds, and the estimation error is less than ±0.02. Under docking road conditions, asymmetric torque distribution suppresses yaw disturbances, maintaining vehicle straight-line stability.

[0068] Compared with the prior art, this application has the following advantages: (1) Improved transmission efficiency: The traditional mechanical transmission chain has been eliminated, and the overall vehicle transmission efficiency has been increased from 85% to 88% to 92% to 95%; (2) Accelerated torque response: The motor torque response time is shortened from 200-500ms to 10-50ms, an improvement of more than 10 times; (3) Improved fuel economy: The adaptive ECMS energy management strategy can achieve an improvement of about 18% in fuel economy, with a difference of less than 5% from the global optimal dynamic programming; (4) Improved yaw stability: The center of mass sideslip angle is controlled within the safety boundary of ±5°, and the yaw rate tracking error is less than 10%; (5) Improved traction performance: Acceleration capability on low-adhesion surfaces is improved by 35% compared to no control, and slip ratio control accuracy is within ±5% of the optimal value; (6) Enhanced system reliability: Six-wheel independent drive achieves six redundancy, and the failure of a single motor does not affect the basic operation of the vehicle; (7) Improved energy recovery: Six-wheel independent regenerative braking increases the braking energy recovery rate by about 30%.

[0069] Please see Figure 5 This application also provides a drive control device for an electric drive system, which can implement the above-described method. The device includes: The acquisition module is used to acquire the driving input commands, vehicle parameters, and battery charge status at the current time step; The power distribution module is used to determine the required power based on the driving input command and the vehicle parameters, and to determine the fuel output power and battery output power based on the battery state of charge and the required power, wherein the battery state of charge and the battery output power are positively correlated. The torque distribution module is used to determine the total drive torque and the additional yaw torque based on the sum of the fuel output power and the battery output power; determine the desired drive torque of several drive motors based on the total drive torque and the additional yaw torque; and generate drive commands based on the desired drive torque.

[0070] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0071] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0072] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0073] Please see Figure 6 , Figure 6 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 601 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 602 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 602 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 602 and is called and executed by the processor 601 using the methods described in the embodiments of this application. The input / output interface 603 is used to implement information input and output; The communication interface 604 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 605 transmits information between various components of the device (e.g., processor 601, memory 602, input / output interface 603, and communication interface 604); The processor 601, memory 602, input / output interface 603, and communication interface 604 are connected to each other within the device via bus 605.

[0074] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0075] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0076] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0077] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0078] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network.

[0079] This application embodiment also provides an electric drive system, the electric drive system comprising: Sensors are used to collect driving input commands, vehicle parameters, and battery state of charge; A controller, configured to perform the steps in the methods described in the above embodiments; A drive motor is communicatively connected to the controller, and the drive motor is used to generate torque according to the torque command output by the controller; The power supply unit is communicatively connected to the controller and is equipped with a generator and a power battery. The power supply unit is used to control the generator and the power battery to output power to the drive motor according to the power distribution command sent by the controller.

[0080] This application also provides an engineering vehicle, which includes a front body, a rear body, and the electric drive system described above. The front body and the rear body are hinged, for example, by a hinge.

[0081] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0082] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0083] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0084] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0085] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0086] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0087] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0088] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0089] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0090] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0091] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A drive control method for an electric drive system, characterized in that, The method includes the following steps: Obtain the driving input commands, vehicle parameters, and battery charge status at the current time step; The required power is determined based on the driving input command and the vehicle parameters, and the fuel output power and battery output power are determined based on the battery state of charge and the required power, wherein the battery state of charge and battery output power are positively correlated. The total drive torque and additional yaw torque are determined based on the sum of the fuel output power and the battery output power; the desired drive torque of several drive motors is determined based on the total drive torque and the additional yaw torque; and drive commands are generated based on the desired drive torque.

2. The method according to claim 1, characterized in that, The step of determining the fuel output power and battery output power based on the battery state of charge and the required power includes: The battery state of charge is input into a pre-built PI controller, and an equivalent factor is determined by the PI controller. The PI controller is configured to perform proportional-integral calculation based on the deviation between the battery state of charge and a reference value. When the battery state of charge is lower than the reference value, the equivalent factor is decreased, and when the battery state of charge is higher than the reference value, the equivalent factor is increased. A first objective function for power distribution calculation is determined based on the equivalent factor, and the first objective function is solved to obtain the fuel output power and the battery output power.

3. The method according to claim 2, characterized in that, The first objective function is determined through the following steps: Construct a first objective function with the goal of minimizing fuel consumption. The first objective function is obtained by adding a first component and a second component. The first component represents the actual fuel consumption of the generator, and the second component represents the equivalent fuel consumption of the battery output power. Determine the constraints of the first objective function.

4. The method according to any one of claims 1 to 3, characterized in that, The step of determining the total drive torque and additional yaw moment based on the sum of the fuel output power and the battery output power includes: The total drive torque is obtained by calculating the sum of the fuel output power and the battery output power; The total driving torque is input into the pre-built trajectory tracking controller, which outputs the hinge angle command. The hinge angle command is input into a pre-built linear quadratic regulator, which outputs the additional yaw moment. The trajectory tracking controller is configured to be based on an articulated vehicle kinematics model, with the goal of minimizing lateral position error and heading angle error, and to obtain the articulation angle command by solving a model predictive control algorithm. The linear quadratic regulator is configured to calculate the desired yaw rate according to the articulation angle command, and to calculate the additional yaw moment by solving the optimal feedback gain matrix, using the center of mass sideslip angle and the state error of the yaw rate as inputs.

5. The method according to any one of claims 1 to 3, characterized in that, The step of determining the desired drive torque of several drive motors based on the total drive torque and the additional yaw moment includes: The total drive torque and the additional yaw moment are input into a pre-constructed quadratic programming controller, which outputs the desired drive torque of several drive motors. The quadratic programming controller is configured to obtain the desired drive torque of several drive motors by solving a second objective function based on minimizing the driving force tracking error, minimizing the yaw moment tracking error, minimizing the tire utilization variance, and minimizing the overall motor loss.

6. The method according to any one of claims 1 to 3, characterized in that, The step of generating drive commands based on the desired drive torque includes: The current road surface type and optimal slip ratio are estimated using a fuzzy observer; The desired driving torque is input into a pre-built sliding mode controller, which outputs a driving command. The sliding mode controller is configured to reduce the driving torque of the current wheel to bring the wheel slip ratio back to the optimal slip ratio when the wheel slip ratio exceeds a threshold.

7. A drive control device for an electric drive system, characterized in that, The device includes: The acquisition module is used to acquire the driving input commands, vehicle parameters, and battery charge status at the current time step; The power distribution module is used to determine the required power based on the driving input command and the vehicle parameters, and to determine the fuel output power and battery output power based on the battery state of charge and the required power, wherein the battery state of charge and battery output power are positively correlated. The torque distribution module is used to determine the total drive torque and the additional yaw torque based on the sum of the fuel output power and the battery output power; determine the desired drive torque of several drive motors based on the total drive torque and the additional yaw torque; and generate drive commands based on the desired drive torque.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 6.

9. An electric drive system, characterized in that, The electric drive system includes: Sensors are used to collect driving input commands, vehicle parameters, and battery state of charge; A controller configured to perform the steps of the method according to any one of claims 1 to 6; A drive motor is communicatively connected to the controller, and the drive motor is used to generate torque according to the torque command output by the controller; The power supply unit is communicatively connected to the controller and is equipped with a generator and a power battery. The power supply unit is used to control the generator and the power battery to output power to the drive motor according to the power distribution command sent by the controller.

10. An engineering vehicle, characterized in that, The engineering vehicle includes a front body, a rear body, and the electric drive system as described in claim 9, wherein the front body and the rear body are hinged together.

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