Vehicle dynamical model-based double-closed-loop detection system for vehicle motor controller

Abstract

The invention provides a vehicle motor controller double-closed-loop detection system based on a vehicle dynamics model. The vehicle motor controller double-closed-loop detection system comprises a torque instruction determination unit, a real-time communication unit, a to-be-detected motor controller and a motor simulator. The torque instruction determination unit determines a torque instruction in a to-be-tested driving scene through closed-loop feedback control based on a preset vehicle dynamics model; the real-time communication unit is used for outputting the torque instruction to the motor controller; and the motor controller is connected with the motor simulator through a coupling network in a dragging manner, and performs closed-loop control on the motor simulator based on a torque instruction received from the real-time communication unit and real-time torque information calculated from a feedback signal of the motor simulator. According to the detection system provided by the invention, the target torque of the vehicle under various actual working conditions can be represented more accurately, and the credibility of a test result is effectively improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of vehicle motor testing, relates to power-level hardware-in-the-loop simulation and testing technology, and specifically provides a vehicle motor controller double closed-loop detection system based on a vehicle dynamics model. Background Art

[0002] Power-HIL testing technology has been widely used in in-the-loop testing of new energy vehicle motors. Generally, the motor controller (MCU) to be tested is connected to the motor simulator (EME) through a coupling network to construct a pair-drag test platform. The motor simulator side simulates the output characteristics of the motor based on the control instructions from the motor controller side through a motor model that can simulate the actual motor performance and the power devices of the actual inverter, and feeds back to the motor controller side, thereby realizing in-the-loop detection of the motor controller.

[0003] The above-mentioned towing test system including the motor controller to be tested and the motor simulator needs to determine its target torque according to the state that the vehicle needs to achieve under starting, steering, braking and other working conditions, and convert it into waveform signals such as target current and voltage through coordinate transformation, which are modulated to form a control signal for the motor simulator. However, the above-mentioned waveform signals used to reflect the changes in working conditions generally adopt a step method. This simple equivalent method is difficult to accurately simulate the changes in target torque caused by acceleration, deceleration, and change of direction during the actual use of the vehicle, which leads to the test results of the motor controller not being consistent with the actual motor working conditions, thereby losing the meaning of using a motor simulator for in-loop testing.

[0004] Therefore, a more accurate characterization is needed based on the target torque of the vehicle under various actual operating conditions so that it can better reflect the characteristics of the motor under actual operating conditions. Summary of the invention

[0005] In order to solve the problems existing in the above-mentioned prior art, the present application provides a dual closed-loop detection system for a vehicle motor controller based on a vehicle dynamics model. The system describes the target torque of the motor under various working conditions through a high-precision vehicle dynamics model, so that its output performance is more in line with the actual working conditions of the real vehicle. The detection system includes a torque command determination unit, a real-time communication unit, a motor controller to be tested, and a motor simulator;

[0006] The torque command determination unit determines the torque command under the driving scenario to be tested through closed-loop feedback control based on a preset vehicle dynamics model;

[0007] The real-time communication unit is used to output the torque command to the motor controller;

[0008] The motor controller and the motor simulator are connected in parallel via a coupling network, and closed-loop control is performed on the motor simulator based on the torque command received from the real-time communication unit and the real-time torque information calculated from the feedback signal of the motor simulator.

[0009] Furthermore, the input of the vehicle dynamics model includes one or more of the driving / braking torque and the steering angle of each wheel included in the vehicle; the output of the vehicle dynamics model includes one or more of the wheel speed, lateral / longitudinal speed, yaw angular velocity and center of mass sideslip angle of each wheel included in the vehicle; the driving scenario to be tested includes one or more of the following scenarios: starting, braking, steering, emergency double lane change, and serpentine penetration.

[0010] Furthermore, the torque command determination unit includes a decision module and a vehicle dynamics model; the decision module is feedback-connected to the vehicle dynamics model, generates an input of the vehicle dynamics model based on an alternative torque command, and adjusts the alternative torque command according to a deviation between an output of the vehicle dynamics model and a driving scenario to be tested, until a decision is made to obtain a torque command for output to the motor controller.

[0011] Preferably, the torque command determination unit further includes a torque constraint module, which is used to receive the torque command and constrain the torque command by cyclically executing the following steps:

[0012] A1, obtain the torque command output by the decision module,

[0013] A2, determining whether the slope of the torque command exceeds the maximum output torque change rate k0 that the vehicle motor can achieve, if so, limiting the change rate of the torque command to k0 and executing the next step, if not, directly executing the next step;

[0014] A3, judging whether the torque command exceeds the maximum torque T0 that the motor can output, if so, limiting the torque command to T0 before outputting, if not, directly outputting the torque command.

[0015] Preferably, when the judgment result of step A2 or step A3 is yes, the torque constraint module further adjusts the driving scenario to be tested.

[0016] Furthermore, the speed at which the torque instruction determination unit outputs the torque instruction is much lower than the speed at which the motor controller resolves the real-time torque.

[0017] Preferably, the torque instruction determination unit also includes an interpolation module, which is connected between the decision module and the real-time communication unit and is used to interpolate the torque instruction output by the decision module, wherein the density of the interpolation points is determined based on the speed at which the motor controller solves the real-time torque.

[0018] Further, there is a communication delay when the torque command is transmitted from the torque command determination unit to the real-time communication unit, and the delay function G1 of the communication delay is shown in the following formula:

[0019]

[0020] Among them, T d1 is the time lag coefficient, and s is the independent variable of Laplace transform.

[0021] Furthermore, the motor controller performs closed-loop control on the motor simulator based on the following steps:

[0022] The first step is to set the desired current on the d-axis Set to 0, and perform feedback control on the torque command and the real-time torque based on the following formula to obtain the desired current of the q-axis

[0023]

[0024] Among them, T ref , T fdb are the torque command and real-time torque respectively, u(t) is the feedback control quantity, k p , k i are the control parameters of the first PI controller respectively;

[0025] In the second step, the d-axis desired current is adjusted using the second PI controller. and the desired current on the q axis Converted to the expected voltage on the d-axis and the expected voltage on the q axis

[0026] The third step is to determine the expected voltage of the α-axis based on the following formula: and the expected voltage on the β axis

[0027]

[0028] in, is the phase angle between the α-axis and the d-axis;

[0029] Step 4: Set the desired voltage on the α axis and the expected voltage on the β axis Using SVPWM algorithm to perform modulation to obtain a switching signal of the inverter in the motor controller;

[0030] The fifth step is to collect the current and voltage on the motor controller side, and generate the d-axis current i based on the control delay function G2 and the motor model transfer function G3 shown in the following formula: d and q-axis current i q :

[0031]

[0032] Among them, T d2 is the time lag coefficient, L s(dq) , R s 、w e are the d-axis and q-axis inductances, stator resistance and angular velocity in the motor model, respectively, and j is an imaginary unit;

[0033] Step 6: d 、i q Perform inverse Park transformation and inverse Clark transformation, obtain the switching signal of the motor simulator through motor control strategy decision, and generate the three-phase current i of the motor simulator a 、i b 、i c And three-phase voltage U a , U b , U c ;

[0034] Step 7: The three-phase voltage U of the motor simulator a , U b , U c After passing through the coupling network, it returns to the motor controller to complete the active power drag cycle of the motor controller under the corresponding working conditions.

[0035] An embodiment of the present application provides a dual closed-loop detection system for a vehicle motor controller based on a vehicle dynamics model. The vehicle dynamics model is introduced into a towing test platform of the vehicle motor controller, and is used to simulate the dynamic behavior of the vehicle motor under the control of a preset torque command. The system compares the model with the driving scenario to be tested to achieve closed-loop feedback adjustment, thereby obtaining the torque command value that the motor should receive under the set working conditions. The torque command is then input into the control closed loop formed by the towing of the motor controller and the motor simulator, thereby ensuring that the evaluation of the motor controller's performance conforms to the actual driving scenario, greatly improving the credibility of the test results. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 The present invention is an architecture diagram of an existing motor controller towing test platform;

[0037] Figure 2 Schematic diagram of wheel load torque in step form;

[0038] Figure 3 A schematic diagram of a dual closed-loop detection system for a vehicle motor controller based on a vehicle dynamics model according to an embodiment of the present application;

[0039] Figure 4 A schematic diagram of a framework of a torque instruction determination unit provided according to an embodiment of the present application;

[0040] Figure 5 A schematic diagram of a framework of a torque instruction determination unit provided according to an embodiment of the present application;

[0041] Figure 6 A flowchart for implementing the constraint on the torque command according to an embodiment of the present application;

[0042] Figure 7 A schematic diagram of a dual closed-loop detection system for a vehicle motor controller based on a vehicle dynamics model according to a specific embodiment of the present application;

[0043] Figure 8 A schematic diagram of setting vehicle model input parameters according to a specific embodiment of the present application;

[0044] Fig. 9 A schematic diagram of setting a data format for communication between Simulink and a NI real-time system according to a specific embodiment of the present application;

[0045] Fig.10 A schematic diagram of a sending configuration for communicating between Simulink and a NI real-time system according to a specific embodiment of the present application;

[0046] Fig.11 A schematic diagram of a receiving configuration for communicating between Simulink and a NI real-time system according to a specific embodiment of the present application;

[0047] Fig.12 A schematic diagram of interpolation processing performed by Simulink through an interpolation algorithm according to a specific embodiment of the present application;

[0048] Fig.13 It is a schematic diagram of the load torque of each wheel provided according to a specific embodiment of the present application. DETAILED DESCRIPTION

[0049] Hereinafter, the present application will be further described based on preferred embodiments with reference to the accompanying drawings.

[0050] In the description of the embodiments of the present application, it should be noted that if the terms "upper", "lower", "inner", "outer", etc. indicate an orientation or positional relationship based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship in which the products of the embodiments of the present application are usually placed when in use, it is only for the convenience of describing the present application and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present application. In addition, for the convenience of understanding, various components on the drawings are enlarged or reduced, but this practice is not intended to limit the scope of protection of the present application.

[0051] The vocabulary in this specification is used to illustrate the embodiments of the present application, but is not intended to limit the present application. It should also be noted that, unless otherwise clearly specified and limited, the terms "disposed", "connected", and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, a direct connection, an indirect connection through an intermediate medium, or a connection between the two elements. For those skilled in the art, the specific meanings of the above terms in this application can be specifically understood.

[0052] In order to better illustrate the improvements of the technical solution of the present application over the prior art, the current power-level hardware-in-the-loop (Power-HIL) testing technology for automotive motors is first introduced.

[0053] Figure 1 A schematic diagram of the framework of an existing motor controller towing test platform is shown in FIG. Figure 1 As shown, the towing test platform mainly includes the MCU under test on the left, the load EME on the right, and a filter coupling network connecting the two. The MCU under test compares the torque command with the real-time torque corresponding to the feedback signal on the EME side, and uses a preset control algorithm to control the switches of each power device in the inverter on the MCU side, thereby generating a control signal for the inverter on the EME side, so that the real-time torque on the EME side can track the torque command.

[0054] Generally, in order to test the control performance of the motor controller under various working conditions, it is necessary to set the torque command to change to simulate the torque conditions under vehicle acceleration, deceleration, steering and other working conditions. For example, when testing the performance of the motor controller under various working conditions, similar Figure 2 The step signal shown simulates parameters such as the load torque of the wheel, thereby determining the torque command.

[0055] Although the above torque command generation method is simple and intuitive, the torque change is unlikely to occur in the actual vehicle acceleration, deceleration and steering process. Figure 2The sudden changes shown cannot be characterized by simple linear changes, but rather present nonlinear and complex changes when the road conditions, vehicle conditions, and motor conditions are coupled with each other. If the torque command that fits the actual driving scenario cannot be used as the motor tracking target, the test results will inevitably fail to accurately evaluate the actual control performance of the MCU.

[0056] To this end, the present application provides a dual closed-loop detection system for a vehicle motor controller based on a vehicle dynamics model. By introducing a high-precision vehicle dynamics model into the in-loop detection architecture, the change in the torque command can be adapted to the motor operating conditions when the vehicle performs real actions under actual road conditions, thereby effectively improving the credibility of the in-loop detection results.

[0057] Figure 3 A dual closed-loop detection system for a vehicle motor controller based on a vehicle dynamics model is provided according to an embodiment of the present application. The system includes a torque command determination unit, a real-time communication unit, a motor controller to be tested, and a motor simulator.

[0058] The torque command determination unit determines the torque command T under the driving scenario to be tested through closed-loop feedback control based on the preset vehicle dynamics model. ref , the real-time communication unit sends the torque command T ref The output is sent to the motor controller, which is connected to the motor simulator through a coupling network and based on the torque command T received from the real-time communication unit ref , and the real-time torque T calculated from the feedback signal of the motor simulator fdb , perform closed-loop control of the motor simulator.

[0059] The above-mentioned detection system provided by the embodiment of the present application introduces the vehicle dynamics model into the towing test platform of the vehicle motor controller, utilizes it to simulate the dynamic behavior of the vehicle motor under the control of a preset torque command, and compares it with the driving scenario to be tested to achieve closed-loop feedback adjustment, thereby obtaining the torque command value that the motor should receive under the set working conditions, and then inputs the torque command into the control closed loop formed by the towing of the motor controller and the motor simulator, thereby ensuring that the evaluation of the motor controller performance conforms to the actual driving scenario, greatly improving the credibility of the test results.

[0060] The specific implementation of each of the above functional modules will be described in detail below in conjunction with the accompanying drawings.

[0061] <Motor torque-vehicle state closed-loop control based on vehicle dynamics model>

[0062] Figure 4FIG. 4 shows a schematic diagram of a torque command determination unit and a method for determining a torque command of a motor based on closed-loop feedback control in some preferred embodiments. Figure 4 As shown, the torque command determination unit includes a decision module and a vehicle dynamics model connected to the decision module for feedback.

[0063] Specifically, after determining the driving scenario to be tested (in the embodiment of the present application, the driving scenario to be tested includes one or more of vehicle starting, braking, steering, emergency double lane change, and serpentine rod penetration), the above-mentioned driving scenario to be tested is further parameterized into the expected state quantity of the vehicle, such as the wheel speed, lateral / longitudinal speed, yaw angular velocity and center of mass sideslip angle of each wheel, etc., which are input into the decision module, and the decision module determines an alternative torque instruction of a motor based on empirical values ​​(such as table lookup) or various estimation algorithms (for example, using a trained deep learning network, etc.), and the decision module further determines the torque instruction applied by the motor to each wheel of the vehicle based on the alternative torque instruction. The decision module is based on the input of the two input ends to the input of the vehicle dynamics model. The driving / braking torque or steering angle of each wheel of the vehicle, after the above input quantity passes through the vehicle dynamics model, the output is the state of the vehicle under the control of the alternative torque command, such as the wheel speed, lateral / longitudinal speed, yaw angular velocity and center of mass sideslip angle of each wheel of the vehicle, and is fed back to the input end of the decision module. The decision module corrects the alternative torque command by comparing the deviation between the alternative torque command and the state of the vehicle in the driving scenario to be tested, until the vehicle state output by the vehicle dynamics model is consistent with the vehicle state in the driving scenario to be tested, and then outputs the torque command at this time to the motor controller, thereby realizing the motor torque command matching the driving scenario to be tested based on closed-loop feedback control.

[0064] The reason for using this closed-loop feedback control to determine the torque command is that existing vehicle dynamics models, such as Carsim, are generally used to characterize the relationship between variables that drive the vehicle and vehicle motion variables. For example, when corresponding control instructions (such as driving torque, braking torque and steering torque) are applied to the two driving wheels or four driving wheels of the vehicle, the change in the motion state (such as speed, acceleration, velocity, angular acceleration) of a vehicle with a specific size and weight, that is: applying certain driving information to each wheel can uniquely obtain the vehicle's motion state information, otherwise there is no one-to-one mapping relationship. For example, when different driving forces are applied to different wheels, the acceleration and deceleration of the vehicle may be similar or even the same. Therefore, the torque command of the motor cannot generally be determined directly from the vehicle's driving scenario, but needs to be obtained by tracking the output of the vehicle dynamics model with the driving scenario to be tested.

[0065] The vehicle dynamics model known to those skilled in the art, such as the commercial software Carsim mentioned above, can be used for the above-mentioned closed-loop feedback. When using the above-mentioned vehicle dynamics model, it is found that the torque command signal obtained by using the vehicle dynamics model such as Carsim still has a gap with the actual vehicle driving state in terms of its signal value range, signal change rate, etc. For example, there is a torque command change rate that is too large, close to a step signal, or the torque command exceeds the maximum torque that the motor can output, etc. In the actual driving process of the vehicle, the motor-driven vehicle is bound to be constrained by its torque change rate and upper limit, that is, some extreme driving conditions are bound to be impossible to achieve. Therefore, in order to better fit the actual output characteristics of the motor and evaluate the rationality of the driving scenario to be tested, such as Figure 5 As shown, the torque command determination unit also includes a torque constraint module to constrain the torque command that deviates too much from the actual vehicle operating condition.

[0066] Figure 6 FIG. 4 shows an implementation flow of the torque constraint module in some embodiments, such as Figure 6 As shown, the torque constraint module constrains the torque command that deviates too much from the actual vehicle operating condition by cyclically executing the following steps:

[0067] A1, obtain the torque command output by the decision module,

[0068] A2, determining whether the slope of the torque command exceeds the maximum output torque change rate k0 that the vehicle motor can achieve, if so, limiting the change rate of the torque command to k0 and executing the next step, if not, directly executing the next step;

[0069] A3, judging whether the torque command exceeds the maximum torque T0 that the motor can output, if so, limiting the torque command to T0 before outputting, if not, directly outputting the torque command.

[0070] Through the above steps, unreasonable torque instructions can be significantly eliminated, thereby effectively improving the feasibility of the detection results.

[0071] In addition, since the occurrence of the above-mentioned exceeding constraint condition generally means that the setting of the driving scene to be tested may exceed the actual vehicle performance limit, therefore, in some preferred embodiments, when the judgment result of step A2 or step A3 is yes, such as Figure 5 As shown, the torque constraint module also adjusts the driving scenario to be tested to make it more consistent with the actual performance of the vehicle.

[0072] <Transmission of Torque Command>

[0073] After the torque command is output, it is output to the motor controller through the real-time communication unit. Generally, the real-time communication unit can be implemented by devices such as NI real-time system. There is a communication delay in the process of transmitting the torque command, which causes a phase difference between the torque command received by the real-time communication unit and the torque command issued by the torque command determination unit. The above delay can be represented by a first-order lag function. For example, it can be represented by the delay function G1 of the following formula:

[0074]

[0075] Among them, T d1 is the time lag coefficient, and s is the independent variable of Laplace transform.

[0076] <Motor controller-motor simulator closed-loop control>

[0077] The above T ref After inputting into the motor controller, the motor controller performs closed-loop control on the motor simulator to track the torque command. The implementation method of performing closed-loop testing on the motor controller and the motor simulator connected to the motor is known to those skilled in the art. For example, the motor controller can be as follows Figure 1 or Figure 3 As shown in the figure, the motor simulator is closed-loop controlled by the following steps:

[0078] The first step is to set the desired current on the d-axis Set to 0, and perform feedback control on the torque command and the real-time torque based on the following formula to obtain the desired current of the q-axis

[0079]

[0080] Among them, T ref , T fdb are the torque command and real-time torque respectively, u(t) is the feedback control quantity, k p , k i are the control parameters of the first PI controller respectively;

[0081] In the second step, the d-axis desired current is adjusted using the second PI controller. and the desired current on the q axis Converted to the expected voltage on the d-axis

[0082] and the expected voltage on the q axis

[0083] The third step is to determine the expected voltage of the α-axis based on the following formula: and the expected voltage on the β axis

[0084]

[0085] in, is the phase angle between the α-axis and the d-axis;

[0086] Step 4: Set the desired voltage on the α axis and the expected voltage on the β axis Using SVPWM algorithm to perform modulation to obtain a switching signal of the inverter in the motor controller;

[0087] The fifth step is to collect the current and voltage on the motor controller side, and generate the d-axis current i based on the control delay function G2 and the motor model transfer function G3 shown in the following formula: d and q-axis current i q :

[0088]

[0089] Among them, T d2 is the time lag coefficient, L s(dq) , R s 、w e are the d-axis and q-axis inductances, stator resistance and angular velocity in the motor model, respectively, and j is an imaginary unit;

[0090] Step 6: d 、i q Perform inverse Park transformation and inverse Clark transformation, obtain the switching signal of the motor simulator through motor control strategy decision, and generate the three-phase current i of the motor simulator a 、i b 、i c And three-phase voltage U a , U b , U c ;

[0091] Step 7: The three-phase voltage U of the motor simulator a , U b , U c After passing through the coupling network, it returns to the motor controller to complete the active power drag cycle of the motor controller under the corresponding working conditions.

[0092] <Test frequency matching>

[0093] Since the detection system uses the torque command T ref To establish a connection between the two control loops, it is necessary to coordinate the input-output frequencies of the two control loops to avoid excessive deviation between the two, which would result in a decrease in detection accuracy.

[0094] For example, the frequency of the output signal of the vehicle dynamics model such as Carsim is generally 1000-2000Hz. At this time, the signal update step of its output port is generally 0.5-1ms, and thus the subsequent torque command T ref The generation and output frequency is limited to 1000-2000Hz. However, since the motor simulator uses FPGA as the control unit, its solution cycle rate is generally 1GHz, which is very different from the Carsim output signal update rate. Therefore, in some preferred embodiments, such as Figure 5 As shown, the torque command determination unit also includes an interpolation module, which generates T through an interpolation algorithm. ref The midpoint data of the sequence is used to make its output frequency match the detection frequency of the control closed loop on the motor controller side.

[0095] It should be noted that Figure 5 The interpolation module shown can be used to output the torque command T ref The sequence can also be used to interpolate the signal output by the vehicle dynamics model. Those skilled in the art can flexibly select the connection position of the interpolation module and the data to be interpolated according to specific needs.

[0096] Considering that the vehicle dynamic parameters will not change significantly in a short time (ms), that is, the slope of the curve will not change suddenly, the interpolation module can use the cubic spline curve interpolation method to obtain other data information between the two sampling points output by the Carsim model. The advantage of this interpolation method is that the line is smooth.

[0097] <Specific Example>

[0098] This embodiment provides a specific dual closed-loop detection system for a vehicle motor controller based on a vehicle dynamics model. Figure 7 The schematic diagram of the system is shown in FIG. Figure 7 As shown, the system builds a high-precision dynamic model of the vehicle through Carsim software, implements the functions of the decision-making module, torque constraint module and interpolation module through the Simulink toolbox in Matlab, and realizes a closed-loop connection with Carsim. It makes decisions based on the driving scenario to be tested and obtains the motor torque command that meets the driving scenario.

[0099] Furthermore, the motor torque command is transmitted through the NI real-time system, and the data format matching operation is performed using the hardware interface of the NI real-time system, and then enters the motor controller-motor simulator pair test platform.

[0100] Specifically, Figure 8FIG. 1 shows the input parameter settings of the four-wheel drive four-wheel rotation vehicle model established by Carsim in this embodiment. The vehicle model can be obtained by adjusting the E-Class Sedan vehicle model in Carsim. The input parameters are as follows: Figure 8 As shown, there are 12 driving and braking torques and four-wheel steering angles of the four wheels, a total of 12.

[0101] Figures 9 to 11 The data format, sending and receiving configurations of the communication between Simulink and the NI real-time system in this embodiment are respectively shown.

[0102] In this embodiment, the output step size of the Carsim model is 1 ms, and accordingly, its update frequency is 1000 Hz. As analyzed above, the solution cycle rate of the motor simulator using FPGA as the control unit is generally 1 GHz, which is very different from the update rate of the Carsim output signal. Therefore, the intermediate point data of the torque command is fitted by the cubic spline interpolation algorithm in Simulink. Fig.12 In a specific embodiment, the interpolation result obtained by the interpolation module using this method is shown.

[0103] Fig.13 The figure shows the change of load torque of the four wheels obtained by Simulink during the test of a double lane change driving scenario in this embodiment. The vehicle model used in the Carsim simulation is E-class Sedan, the simulation starting speed is 50km / h, and the road adhesion coefficient is 0.85. When the starting time of the step response is 1s, the amplitude is 8. By comparison Fig.13 and Figure 8 It can be seen that by using the test system of the present application, it is possible to output torque instructions that are more in line with actual working conditions to the motor controller, thereby effectively improving the accuracy and credibility of the motor controller test results.

[0104] The above is a detailed introduction to the specific implementation methods of the present application. For those skilled in the art, several improvements and modifications may be made to the present application without departing from the principles of the present application. These improvements and modifications also fall within the scope of protection of the claims of the present application.

Claims

1. A dual closed-loop detection system for a motor controller for a vehicle based on a vehicle dynamics model, used to test the control performance of the motor controller in a driving scenario to be tested, characterized in that: It includes a torque command determination unit, a real-time communication unit, a motor controller to be tested, and a motor simulator; The torque command determination unit determines the torque command under the driving scenario to be tested through closed-loop feedback control based on a preset vehicle dynamics model; The real-time communication unit is used to output the torque command to the motor controller; The motor controller and the motor simulator are connected in parallel via a coupling network, and closed-loop control is performed on the motor simulator based on the torque command received from the real-time communication unit and the real-time torque information calculated from the feedback signal of the motor simulator.

2. The vehicle motor controller double closed-loop detection system based on the vehicle dynamics model according to claim 1 is characterized in that: The input quantity of the vehicle dynamics model includes one or more of the driving / braking torque and the steering angle of each wheel included in the vehicle; The output of the vehicle dynamics model includes one or more of the wheel speed, lateral / longitudinal speed, yaw rate and center of mass sideslip angle of each wheel included in the vehicle; The driving scenario to be tested includes one or more of the following scenarios: starting, braking, turning, emergency double lane change, and serpentine crossing.

3. The vehicle motor controller double closed-loop detection system based on vehicle dynamics model according to claim 2 is characterized in that: The torque command determination unit includes a decision module and a vehicle dynamics model; The decision module is feedback-connected to the vehicle dynamics model, generates an input of the vehicle dynamics model based on an alternative torque command, and adjusts the alternative torque command according to a deviation between an output of the vehicle dynamics model and a driving scenario to be tested, until a torque command for output to the motor controller is obtained by decision.

4. The vehicle motor controller double closed-loop detection system based on vehicle dynamics model according to claim 2 is characterized in that: The torque command determination unit further includes a torque constraint module, which is used to receive the torque command and constrain the torque command by cyclically executing the following steps: A1, obtain the torque command output by the decision module, A2, determining whether the slope of the torque command exceeds the maximum output torque change rate k0 that the vehicle motor can achieve, if so, limiting the change rate of the torque command to k0 and executing the next step, if not, directly executing the next step; A3, judging whether the torque command exceeds the maximum torque T0 that the motor can output, if so, limiting the torque command to T0 before outputting, if not, directly outputting the torque command.

5. The vehicle motor controller double closed-loop detection system based on vehicle dynamics model according to claim 4 is characterized in that: When the judgment result of step A2 or step A3 is yes, the torque constraint module further adjusts the driving scenario to be tested.

6. The vehicle motor controller double closed-loop detection system based on vehicle dynamics model according to claim 3 is characterized in that: The speed at which the torque command determination unit outputs the torque command is much slower than the speed at which the motor controller resolves the real-time torque.

7. The vehicle motor controller double closed-loop detection system based on vehicle dynamics model according to claim 6 is characterized in that: The torque instruction determination unit also includes an interpolation module, which is connected between the decision module and the real-time communication unit and is used to interpolate the torque instruction output by the decision module, wherein the density of the interpolation points is determined based on the speed at which the motor controller solves the real-time torque.

8. The vehicle motor controller double closed-loop detection system based on vehicle dynamics model according to claim 1 is characterized in that: There is a communication delay when the torque command is transmitted from the torque command determination unit to the real-time communication unit. The delay function G1 of the communication delay is shown in the following formula: Among them, T d1 is the time lag coefficient, and s is the independent variable of Laplace transform.

9. The vehicle motor controller double closed-loop detection system based on vehicle dynamics model according to claim 1, characterized in that: The motor controller performs closed-loop control on the motor simulator based on the following steps: The first step is to set the desired current on the d-axis Set to 0, and perform feedback control on the torque command and the real-time torque based on the following formula to obtain the desired current of the q-axis Among them, T ref , T fdb are the torque command and real-time torque respectively, u(t) is the feedback control quantity, k p , k i are the control parameters of the first PI controller respectively; In the second step, the d-axis desired current is adjusted using the second PI controller. and the desired current on the q axis Converted to the expected voltage on the d-axis and the expected voltage on the q axis The third step is to determine the expected voltage of the α-axis based on the following formula: and the expected voltage on the β axis in, is the phase angle between the α-axis and the d-axis; Step 4: Set the desired voltage on the α axis and the expected voltage on the β axis Using SVPWM algorithm to perform modulation to obtain a switching signal of the inverter in the motor controller; The fifth step is to collect the current and voltage on the motor controller side, and generate the d-axis current i based on the control delay function G2 and the motor model transfer function G3 shown in the following formula: d and q-axis current i q : Among them, T d2 is the time lag coefficient, L s(dq) , R s 、w e are the d-axis and q-axis inductances, stator resistance and angular velocity in the motor model, respectively, and j is an imaginary unit; Step 6: d 、i q Perform inverse Park transformation and inverse Clark transformation, obtain the switching signal of the motor simulator through motor control strategy decision, and generate the three-phase current i of the motor simulator a 、i b 、i c And three-phase voltage U a , U b , U c ; Step 7: The three-phase voltage U of the motor simulator a , U b , U c After passing through the coupling network, it returns to the motor controller to complete the active power drag cycle of the motor controller under the corresponding working conditions.

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