Dual-closed-loop Detection System for Vehicle Motor Controller Based on Vehicle Dynamics Model

Abstract

The present application provides a dual-closed-loop detection system for a vehicle motor controller based on a vehicle dynamics model, including 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 a torque command in a to-be-tested driving scenario 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 a coupled network for drag connection, and 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, closed-loop control is performed on the motor simulator. The detection system provided by the present application can more accurately characterize the target torque of the vehicle under various actual working conditions, effectively improving the credibility of the test results.

Description

Technical Field

[0001] The present invention belongs to the technical field of vehicle motor testing, and relates to power-level hardware-in-the-loop simulation and testing technologies. Specifically, it provides a dual-loop detection system for vehicle motor controllers based on a vehicle dynamics model. Background Art

[0002] The power-level hardware-in-the-loop (Power-HIL) testing technology has currently been widely applied to the in-the-loop testing of new energy vehicle motors. Generally, a counter-rotating test platform is constructed by connecting the motor controller under test (MCU) and the motor emulator (EME) through a coupling network. On the motor emulator side, based on the control instructions from the motor controller side, the output characteristics of the motor are simulated through a motor model capable of simulating the performance of a real motor and the power devices of a real inverter, and then fed back to the motor controller side, thereby realizing the in-the-loop detection of the motor controller.

[0003] For the above counter-rotating test system including the motor controller under test and the motor emulator, it is necessary to determine the target torque according to the states required by the vehicle under conditions such as starting, steering, and braking, and convert it into waveform signals such as target current and voltage through coordinate transformation. After modulation, they are formed into control signals for the motor emulator. However, the above waveform signals used to reflect the changes in working conditions generally adopt a step-by-step method. This simple equivalent method is difficult to accurately simulate the changes in target torque caused by acceleration, deceleration, and direction change during the actual use of the vehicle, and further leads to the test results of the motor controller not conforming to the actual working conditions of the real motor, thus losing the significance of using the motor emulator for in-the-loop testing.

[0004] Therefore, it is necessary to more accurately characterize the target torque of the motor under various actual working conditions of the vehicle so that it can better reflect the characteristics of the motor under real working 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-loop detection system for vehicle motor controllers based on a vehicle dynamics model. This 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 a real vehicle. The detection system includes a torque command determination unit, a real-time communication unit, the motor controller under test, and a motor emulator;

[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 a back-to-back manner through a coupling network. 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, a closed-loop control is performed on the motor simulator.

[0009] Further, the input quantities of the vehicle dynamics model include one or more of the driving / braking torques and steering angles of each wheel included in the vehicle; the output quantities of the vehicle dynamics model include one or more of the wheel speeds, lateral / longitudinal speeds, yaw angular velocities, and center-of-mass sideslip angles of each wheel included in the vehicle; the driving scenarios to be tested include one or more of the following scenarios: starting, braking, steering, emergency double lane change, and slalom.

[0010] Further, the torque command determination unit includes a decision-making module and a vehicle dynamics model; the decision-making module is feedback-connected to the vehicle dynamics model, generates the input quantities of the vehicle dynamics model based on alternative torque commands, and adjusts the alternative torque commands according to the deviation between the output quantities of the vehicle dynamics model and the driving scenarios to be tested until a torque command for output to the motor controller is determined.

[0011] Preferably, the torque command determination unit further includes a torque constraint module, and the torque constraint module 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-making module.

[0013] A2. Determine whether the slope of the torque command exceeds the maximum output torque change rate k0 that the vehicle motor can reach. If so, limit the change rate of the torque command to k0 and execute the next step; if not, directly execute the next step.

[0014] A3. Determine whether the torque command exceeds the maximum torque T0 that the motor can output. If so, limit the torque command to T0 and then output it; if not, directly output the torque command.

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

[0016] Further, the speed at which the torque command determination unit outputs the torque command is much lower than the speed at which the motor controller calculates the real-time torque.

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

[0018] Furthermore, 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 as follows:

[0019]

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

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

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

[0023]

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

[0025] In the second step, the second PI controller is used to convert the d-axis desired current and the q-axis desired current into the d-axis desired voltage and the q-axis desired voltage

[0026] In the third step, the α-axis desired voltage and the β-axis desired voltage

[0027]

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

[0029] In the fourth step, the α-axis desired voltage and the β-axis desired voltage Modulate using the SVPWM algorithm to obtain the switching signals of the inverter in the motor controller;

[0030] In the fifth step, collect the current and voltage on the motor controller side, and generate the d-axis current i d and the q-axis current i q :

[0031]

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

[0033] In the sixth step, perform inverse Park transformation and inverse Clark transformation on i d , i q , and obtain the switching signals of the motor simulator through motor control strategy decision-making, and generate the three-phase currents i a , i b , i c and the three-phase voltages U a , U b , U c ;

[0034] In the seventh step, the three-phase voltages U a , U b , U c of the motor simulator pass through the coupling network and then return to the motor controller to complete the active counter-dragging cycle of the motor controller under the corresponding working conditions.

[0035] An on-vehicle motor controller double closed-loop detection system based on a vehicle dynamics model provided by an embodiment of the present application introduces the vehicle dynamics model into the counter-dragging test platform of the on-vehicle motor controller, uses it to simulate the dynamic behavior of the vehicle motor under a preset torque command control, and compares it with the driving scenario to be tested to achieve closed-loop feedback regulation, so as to obtain the torque command value that the motor should receive under the set working conditions, and then input this torque command into the control closed-loop formed by the counter-dragging of the motor controller and the motor simulator, thereby ensuring that the evaluation of the performance of the motor controller conforms to the actual driving scenario and greatly improving the credibility of the test results. Description of the Drawings

[0036] Figure 1 is an architecture diagram of an existing counter-dragging test platform for a motor controller;

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

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

[0039] Figure 4 Schematic diagram of the framework of the torque command determination unit according to an embodiment of the present application;

[0040] Figure 5 Schematic diagram of the framework of the torque command determination unit according to an embodiment of the present application;

[0041] Figure 6 Flowchart of the implementation for constraining the torque command according to an embodiment of the present application;

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

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

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

[0045] Figure 10 Schematic diagram of the sending configuration for communication between Simulink and the NI real-time system according to a specific embodiment of the present application;

[0046] Figure 11 Schematic diagram of the receiving configuration for communication between Simulink and the NI real-time system according to a specific embodiment of the present application;

[0047] Figure 12 Schematic diagram of the interpolation processing by Simulink using an interpolation algorithm according to a specific embodiment of the present application;

[0048] Figure 13 Schematic diagram of the load torque of each wheel according to a specific embodiment of the present application. Detailed implementation manner

[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 terms such as "upper", "lower", "inner", "outer", etc. indicate the 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 habitually placed during use, it is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be construed as a limitation to the present application. In addition, for the convenience of understanding, various components in the drawings are enlarged or reduced, but this approach is not intended to limit the protection scope of the present application.

[0051] The terms used in this specification are for the purpose of describing the embodiments of the present application, but are not intended to limit the present application. It should also be noted that unless otherwise clearly specified and defined, if terms such as "set", "connected", "coupled" are used, they 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, or an indirect connection through an intermediate medium, and it can be the communication inside two elements. For those skilled in the art, the specific meanings of the above terms in the present application can be specifically understood.

[0052] To better illustrate the improvements of the technical solution of the present application over the prior art, first, the power hardware-in-the-loop (Power-HIL) test technology of current vehicle motors is introduced.

[0053] Figure 1 As shown in the schematic diagram of the framework of an existing motor controller back-to-back test platform, Figure 1 This back-to-back test platform mainly includes the measured MCU on the left, the load EME on the right, and the filter coupling network connecting the two. Among them, the measured MCU 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 switching of each power device in the MCU-side inverter, and then generates a control signal for the EME-side inverter, 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 on the motor 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, currently when testing the performance of the motor controller under various working conditions, a step signal similar to Figure 2 is usually used to simulate parameters such as the load torque of the wheel, and then the torque command is determined.

[0055] Although the above method for generating the torque command is simple and intuitive, in the actual vehicle acceleration, deceleration and steering processes, the torque change cannot occur as Figure 2The mutations shown generally cannot be characterized by simple linear changes either. Instead, they exhibit non-linear complex changes under the coupling of road conditions, vehicle conditions, and motor conditions. If a torque command that fits the actual driving scenario cannot be used as the tracking target for the motor, the test results will surely be unable to accurately evaluate the actual control performance of the MCU.

[0056] For this reason, 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 of the torque command can fit the motor 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 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] Among them, the torque command determination unit determines the torque command T in the to-be-tested driving scenario based on a preset vehicle dynamics model through closed-loop feedback control ref , and the real-time communication unit outputs the torque command T ref to the motor controller. The motor controller is connected in a drag-and-tow manner with the motor simulator through a coupling network, and based on the torque command T ref received from the real-time communication unit, and the real-time torque T fdb calculated from the feedback signal of the motor simulator, performs closed-loop control on the motor simulator.

[0059] Through the above detection system provided by the embodiments of the present application, by introducing a vehicle dynamics model into the drag-and-tow test platform of a vehicle motor controller, using it to simulate the dynamic behavior of the vehicle motor under the control of a preset torque command, and comparing it with the to-be-tested driving scenario to achieve closed-loop feedback regulation, thereby obtaining the torque command value that the motor should receive under the set working conditions. Then, this torque command is input into the control closed-loop formed by the drag-and-tow of the motor controller and the motor simulator, thereby ensuring that the evaluation of the performance of the motor controller conforms to the actual driving scenario and greatly improving the credibility of the test results.

[0060] The following will elaborate on the specific implementation manners of the above various functional modules in conjunction with the accompanying drawings.

[0061] <Motor Torque-Vehicle State Closed-Loop Control Based on Vehicle Dynamics Model>

[0062] Figure 4shows, in some preferred embodiments, a schematic diagram of the framework of the torque command determination unit and its determination of the torque command of the motor based on closed-loop feedback control, as Figure 4 shown, the torque command determination unit includes a decision-making module and a vehicle dynamics model feedback-connected thereto.

[0063] Specifically, after determining the to-be-tested driving scenario (in the embodiments of the present application, the to-be-tested driving scenario includes one or more of vehicle start, braking, steering, emergency double lane change, and slalom), the above to-be-tested driving scenario is further parameterized into the expected state quantities of the vehicle, such as the wheel speeds of each wheel, lateral / longitudinal speeds, yaw angular velocity, and sideslip angle of the center of mass, etc. After inputting into the decision-making module, the decision-making module determines an alternative torque command of a motor based on empirical values (such as looking up tables) or various estimation algorithms (such as using a trained deep learning network, etc.). The decision-making module further determines the driving / braking torques or angles of rotation applied by the motor to each wheel of the vehicle according to the alternative torque command. Based on the input of the two at the input end, the driving / braking torques or angles of rotation of each wheel included in the input vehicle are input into the vehicle dynamics model. After passing through the vehicle dynamics model, the output is the state of the vehicle under the control of the alternative torque command, such as one or more of the wheel speeds of each wheel included in the vehicle, lateral / longitudinal speeds, yaw angular velocity, and sideslip angle of the center of mass, and is fed back to the input end of the decision-making module. The decision-making module corrects the alternative torque command by comparing the deviation between it and the state of the vehicle in the to-be-tested driving scenario until the state of the vehicle output by the vehicle dynamics model is consistent with the state of the vehicle in the to-be-tested driving scenario, and then outputs the torque command at this time to the motor controller, thereby realizing the acquisition of the motor torque command matching the to-be-tested driving scenario based on closed-loop feedback control.

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

[0065] The vehicle dynamics models known to those skilled in the art can be used, such as commercial software like Carsim described above, to perform the above-mentioned closed-loop feedback. When using the above vehicle dynamics models, it is found that there are still gaps between the torque command signals obtained using vehicle dynamics models such as Carsim and the actual vehicle driving state in terms of their signal value ranges, signal change rates, etc. For example, there may be an excessive change rate of the torque command, approximating a step signal, or the torque command exceeding the maximum torque that the motor can output. During the actual driving process of the vehicle, the motor driving the vehicle is bound to be restricted by its torque change rate and upper limit, that is, certain extreme driving conditions cannot be achieved. Therefore, in order to better fit the actual output characteristics of the motor and evaluate the rationality of the driving scenario to be measured, as Figure 5 shown, the torque command determination unit further includes a torque constraint module to constrain the torque command that deviates too much from the actual vehicle operating conditions.

[0066] Figure 6 Illustrates the implementation process of the torque constraint module in some embodiments. As Figure 6 shown, the torque constraint module constrains the torque command that deviates too much from the actual vehicle operating conditions by cyclically performing the following steps:

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

[0068] A2, Determine whether the slope of the torque command exceeds the maximum output torque change rate k0 that the vehicle motor can reach. If so, limit the change rate of the torque command to k0 and perform the next step. If not, directly perform the next step.

[0069] A3, Determine whether the torque command exceeds the maximum torque T0 that the motor can output. If so, limit the torque command to T0 and then output it. If not, directly output the torque command.

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

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

[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 the NI real-time system. Among them, there is a communication delay in the process of torque command transmission, resulting in 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] Where, T d1 is the time lag coefficient, and s is the independent variable of the Laplace transform.

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

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

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

[0079]

[0080] Where, T ref , T fdb are the torque command and the 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] The second step is to use the second PI controller to convert the d-axis desired current and the q-axis desired current into the d-axis desired voltage

[0082] and the q-axis desired voltage

[0083] The third step is to determine the α-axis desired voltage and the β-axis desired voltage

[0084]

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

[0086] In the fourth step, the desired α-axis voltage and the desired β-axis voltage are modulated using the SVPWM algorithm to obtain the switching signals of the inverter in the motor controller;

[0087] In the fifth step, the current and voltage on the motor controller side are collected, and the d-axis current i d and the q-axis current i q are generated based on the control delay function G2 shown in the following formula and the motor model transfer function G3:

[0088]

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

[0090] In the sixth step, the inverse Park transformation and inverse Clark transformation are performed on i d , i q , and the switching signals of the motor simulator are obtained through the motor control strategy decision-making, and the three-phase current i a , i b , i c and the three-phase voltage U a , U b , U c of the motor simulator are generated;

[0091] In the seventh step, the three-phase voltages U a , U b , U c of the motor simulator pass through the coupling network and then return to the motor controller to complete the active counter-dragging cycle of the motor controller under the corresponding working conditions.

[0092] <Test frequency matching>

[0093] Since this detection system establishes the connection between the two control closed loops through the torque command T ref , it is necessary to coordinate the input-output frequencies of the two control closed loops to avoid excessive deviation between the two, resulting in a decrease in detection accuracy.

[0094] For example, the frequency of the output signal of a vehicle dynamics model such as Carsim is generally 1000 - 2000 Hz. At this time, the signal update step of its output port is generally 0.5 - 1 ms, and thus the subsequent torque command T ref The generation and output frequency are limited to 1000 - 2000 Hz. However, since the motor simulator uses an FPGA as the control unit, its calculation cycle rate is generally 1 GHz, which is very different from the output signal update rate of Carsim. Therefore, in some preferred embodiments, as Figure 5 shown, the torque command determination unit further includes an interpolation module, which interpolates and generates the intermediate point data of the T ref sequence through an interpolation algorithm 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 interpolate the output torque command T ref sequence, or can 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 for interpolation according to specific needs.

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

[0097] <Specific Embodiment>

[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 framework schematic diagram of the system is shown. As Figure 7 shown, the system constructs a high-precision dynamics model of the vehicle through Carsim software, realizes 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 to make decisions according to the driving scenarios to be tested and obtain the motor torque command that meets the driving scenarios.

[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 it enters the motor controller - motor simulator co-simulation test platform.

[0100] Specifically, Figure 8It shows the setting of input parameters of the four-wheel drive and four-wheel steering vehicle model established by Carsim in this embodiment. This vehicle model can be obtained by adjusting the E-Class Sedan vehicle model in Carsim, and its input quantities are as Figure 8 shown, which are the driving, braking torques and four-wheel steering angles of the four wheels, a total of 12.

[0101] Figures 9 to 11 It respectively shows the data format of communication between Simulink and the NI real-time system, as well as the configuration of sending and receiving in this embodiment.

[0102] In this embodiment, the output step of the Carsim model is 1 ms. Correspondingly, its update frequency is 1000 Hz. As analyzed before, 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. Figure 12 It shows the interpolation result obtained by the interpolation module using this method in a specific embodiment.

[0103] Figure 13 It shows the change of the load torques 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 starting vehicle speed of the simulation is 50 km / h, and the road adhesion coefficient is 0.85. When the starting time of the step response is 1 s, the amplitude is 8. By comparing Figure 13 with Figure 8 it can be known that using the test system of the present application can output a torque command that is more in line with the actual working conditions to the motor controller, thereby effectively improving the accuracy and reliability of the test results of the motor controller.

[0104] The above has introduced the specific implementation manners of the present application in detail. For those skilled in the art of this technology, without departing from the principle of the present application, several improvements and modifications can still be made to the present application, and these improvements and modifications also belong to the protection scope 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 is connected to the motor simulator via a coupling network, and performs closed-loop control on the motor simulator based on the torque command received from the real-time communication unit and the real-time torque information obtained by solving the feedback signal of the motor simulator; 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 outputting to the motor controller is obtained by decision; 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.

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 1 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.

4. The vehicle motor controller double closed-loop detection system based on vehicle dynamics model according to claim 1 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.

5. The vehicle motor controller double closed-loop detection system based on vehicle dynamics model according to claim 4 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.

6. 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.

7. The vehicle motor controller double closed-loop detection system based on vehicle dynamics model according to claim 1 is 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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