Method for controlling torque of switched reluctance motor

Abstract

The invention discloses a method for controlling the torque of a switched reluctance motor, which improves the parameter acquisition precision through composite filtering preprocessing, optimizes the overlapping distribution of the torque in a commutation region in combination with a fuzzy PID adaptive torque distribution strategy, effectively inhibits the jump of the commutation torque, effectively reduces the torque ripple coefficient, and greatly reduces the torque ripple coefficient compared with the traditional direct torque control method. And the operation stability and noise level of the motor are obviously improved.

Description

Technical Field

[0001] This invention belongs to the field of switched reluctance motor drive control technology, and relates to a method for controlling the torque of a switched reluctance motor. Background Technology

[0002] Switched reluctance motors, with their doubly salient pole stator and rotor structure, absence of permanent magnets, and simple windings, possess advantages such as low manufacturing cost, high reliability, wide speed range, strong fault tolerance, and high temperature resistance, making them widely applicable in industrial drives, transportation, aerospace, and other fields. However, due to the inherent doubly salient pole structure leading to severe magnetic circuit saturation and nonlinear inductance, significant torque output pulsation occurs, resulting in motor vibration and noise. This defect severely limits their widespread application in scenarios with high requirements for operational comfort.

[0003] To address the torque ripple problem, existing technologies have proposed various control strategies, which can be mainly divided into two categories: one is based on the optimization of the motor body structure, which improves electromagnetic characteristics by adjusting the stator and rotor pole shapes, air gap parameters, etc. However, this type of method has a long design cycle, high manufacturing cost, and limited adaptability; the other is based on the optimization of control strategies, including direct instantaneous torque control, torque distribution function control, and direct torque control.

[0004] Existing control strategies still have many shortcomings: Traditional direct instantaneous torque control uses hysteresis regulation, which has a fast response speed, but the switching frequency is not fixed and is easily affected by the hysteresis error limit, leading to fluctuations in control accuracy; torque distribution function control requires a complex phase current inverse calculation process, has a slow response speed, and is highly dependent on the torque-current-position characteristic curve; in conventional direct torque control, the flux linkage and torque observation accuracy are easily affected by the nonlinear parameters of the motor, and negative torque is prone to occur in the commutation region, leading to increased pulsation; some improved schemes introduce intelligent algorithms such as neural networks and genetic algorithms, which can improve the control effect, but have problems such as excessive computation and poor real-time performance, making it difficult to meet the needs of engineering applications. In addition, existing control methods are not adaptable enough to dynamic conditions such as sudden load changes and rapid speed changes, and the control performance is prone to deterioration when motor parameters change with temperature.

[0005] Therefore, there is an urgent need for a torque control method for switched reluctance motors that takes into account torque ripple suppression, control accuracy, dynamic response performance and parameter robustness, and is simple in structure, computationally efficient and easy to implement in engineering, so as to overcome the shortcomings of existing technologies. Summary of the Invention

[0006] In order to overcome the shortcomings of the prior art, the present invention provides a method for controlling the torque of a switched reluctance motor.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: A method for controlling the torque of a switched reluctance motor includes the following steps: Step 1: After the system is powered on, it completes hardware self-test, core parameter configuration, feature data table loading, and standby readiness. Step 2: Collect rotor position pulse signals and stator current analog signals of each phase according to the set cycle, and identify the operating conditions after preprocessing; Step 3: Smooth the target torque command and dynamically allocate the torque weight of each phase based on the operating conditions and torque error; Step 4: Obtain the initial torque observation value based on the rotor position signal and phase current signal, optimize the output real-time torque observation value, calculate the error and generate the current correction command; Step 5: Convert the current correction command into a PWM drive signal to drive the motor and monitor the safety status in real time; Step 6: Iterate through steps 2 to 5 to achieve closed-loop feedback regulation.

[0008] Furthermore, in step 2, the preprocessing includes: performing moving average filtering on the position pulse signal to eliminate high-frequency noise, optimizing signal smoothness through Kalman filtering, and outputting the rotor position angle; performing zero-point drift correction on the current analog signal, subtracting the static zero-point voltage, calibrating the amplitude to 0-3.3V through a signal conditioning circuit, converting it into a 12-bit digital signal via an ADC, eliminating interference through composite filtering, and outputting the phase current value.

[0009] Furthermore, the operating condition identification method in step 2 is as follows: calculate the real-time load based on the preprocessed speed and current signals, and classify the steady-state operating condition type according to the speed and load size; determine whether it is a sudden load transition condition by monitoring the load change in adjacent control cycles.

[0010] Furthermore, step 3, torque weight allocation, includes: dividing the conducting phase region and commutation transition region based on the rotor position angle, and determining the initial torque allocation weight of each phase; the fuzzy PID adaptive torque allocation module reads the real-time torque error and speed change rate from the data buffer, calculates the PID parameter correction amount and adjusts the PID parameters, and dynamically optimizes the torque allocation weight of each phase.

[0011] Furthermore, the calculation of PID parameter correction includes: using real-time torque error and speed change rate, through a preset 5×5 fuzzy rules, including a large positive torque error, a small positive speed change rate, corresponding to an increase of 0.2 in proportional gain, an increase of 0.02 in integral gain, and an increase of 0.05 in derivative gain, the calculation is performed using the Mamdani inference method.

[0012] Furthermore, in step 4, the preprocessed phase current and rotor position signals are read, and the flux linkage-current-position characteristic data table in the on-chip RAM is looked up using the lookup table interpolation method to obtain the real-time flux linkage value; the initial torque observation value is derived by combining the torque formula of the switched reluctance motor, and the extended Kalman filter algorithm is introduced to optimize the initial torque observation value, and the optimized real-time torque observation value is output; the difference between the optimized real-time torque observation value and the target torque value of each phase is calculated, the torque observation value is dynamically corrected, and a current correction command is generated.

[0013] Furthermore, in step 5: read the current correction command for each phase, adopt the improved SVPWM modulation algorithm, calculate the action time of the voltage vector of each phase according to the current command, the modulation algorithm includes converting the three-phase current into two-phase stationary coordinate system current through Clark transformation, and then converting it into synchronous rotating coordinate system current through Park transformation, calculating the voltage vector amplitude and angle, and generating PWM drive signal.

[0014] Furthermore, the closed-loop feedback adjustment in step 6 is iterated at intervals set by the control cycle; if the host computer issues a new target torque command, the process is re-executed starting from the command smoothing process in step 3; if a stop command or fault alarm is detected, the loop is terminated, the drive signal is cut off, and the system enters a stop state.

[0015] In summary, the advantages of this invention are: This invention improves parameter acquisition accuracy through composite filtering preprocessing, and optimizes torque overlap distribution in the commutation zone by combining fuzzy PID adaptive torque distribution strategy, effectively suppressing commutation torque jumps and effectively reducing the torque ripple coefficient. Compared with the traditional direct torque control method, it is significantly reduced, which significantly improves the motor's running stability and noise level.

[0016] An improved torque observation and error compensation module is adopted, which integrates lookup table interpolation and extended Kalman filtering to improve torque observation accuracy; the fuzzy PID adaptive adjustment algorithm can optimize control parameters in real time according to changes in operating conditions, reduce the impact of motor parameters on control performance as temperature and load change, and stabilize and reduce torque control error.

[0017] By smoothing torque commands and adaptive torque distribution under operating conditions, the torque tracking capability under dynamic operating conditions such as sudden load changes and rapid speed changes is improved, and the torque adjustment time is significantly shortened when the load changes. Attached Figure Description

[0018] Figure 1 This is a flowchart of the torque control method for a switched reluctance motor according to the present invention. Detailed Implementation

[0019] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0020] This invention provides a method for controlling the torque of a switched reluctance motor, based on a control system consisting of a sensing layer, a control layer, and an execution layer, to achieve precise and stable torque control.

[0021] The perception layer includes a sensor module, a signal preprocessing module, and a working condition identification submodule. These modules are connected and interact with each other via a high-speed data bus and an analog signal link. The sensor module employs a multi-sensor fusion configuration, including an incremental photoelectric encoder, a Hall current sensor, and a speed calculation submodule. The incremental photoelectric encoder is fixed to the rotor shaft end of the switched reluctance motor to acquire real-time rotor position signals. The Hall current sensor is connected in series in the connection circuit between the power converter and the motor stator windings to acquire stator current signals for each phase. The speed calculation submodule is integrated within the signal preprocessing module, deriving the real-time speed based on the time change rate of the rotor position signal. The signal preprocessing module incorporates a composite filtering unit and a signal conditioning unit. The composite filtering unit eliminates high-frequency noise and random interference in the position and current signals, while the signal conditioning unit performs amplitude calibration, zero-point drift correction, and analog-to-digital conversion on the current signal. The operating condition identification submodule determines the motor's operating status based on the preprocessed position, speed, and current signals, using preset operating condition thresholds.

[0022] The signal output of the incremental photoelectric encoder is connected to the encoder interface of the signal preprocessing module via a differential signal line, transmitting the original position pulse signal to the preprocessing module. The analog signal output of the Hall current sensor is connected to the analog input interface of the signal preprocessing module via a shielded signal line, and the original current signal is converted into a standard digital signal of 0-3.3V by the signal conditioning unit. The signal preprocessing module establishes bidirectional communication with the core controller of the control layer via the SPI bus. On the one hand, it uploads the preprocessed position, speed, and current digital signals to the control layer, and on the other hand, it receives the filter parameter configuration instructions (such as filter window size and threshold parameters) issued by the control layer. The operating condition recognition submodule interacts directly with the signal preprocessing module through the internal data bus to obtain the preprocessed operating parameters in real time. The recognition result is fed back to the torque command planning module of the control layer through the on-chip interrupt signal.

[0023] The control layer integrates the core controller and the torque command planning module, fuzzy PID adaptive torque allocation module, improved torque observation and error compensation module, and safety protection decision module deployed within the controller. Each module interacts with the controller through the on-chip bus and establishes connections with the perception layer and execution layer through external interfaces.

[0024] The core controller uses a DSP chip as the operating platform for each functional module, responsible for data processing and instruction generation; the torque instruction planning module receives the target torque instruction issued by the host computer and performs smoothing processing based on the operating condition identification results; the fuzzy PID adaptive torque allocation module dynamically adjusts the torque weight of each phase based on torque error and speed change rate; the improved torque observation and error compensation module realizes accurate observation and error correction of real-time torque; and the safety protection decision module monitors operating parameters and triggers abnormal operating condition protection mechanisms.

[0025] The core controller establishes one-way communication with the host computer via the UART bus to receive the target torque command issued by the host computer; it receives the preprocessed operating parameters and operating condition identification results from the perception layer via the SPI bus as input data for each decision module; the functional modules share data through the on-chip AXI bus: the smoothed torque command from the torque command planning module is transmitted to the fuzzy PID adaptive torque allocation module, the torque allocation weight from the fuzzy PID module is transmitted to the improved torque observation and error compensation module, and the current correction command from the error compensation module is transmitted to the execution layer; the safety protection decision module obtains the operating status data of each module in real time through the internal interrupt link, and when an abnormality is detected, it outputs a protection trigger signal to the drive module of the execution layer through the GPIO port, and at the same time feeds back alarm information to the host computer via the UART bus.

[0026] The execution layer includes an optimized PWM drive module, a power conversion module, and a status monitoring sub-module. Each module is connected to the power supply link through a drive link and interacts with the control layer through a feedback link.

[0027] The optimized PWM drive module receives current correction commands from the control layer and generates PWM drive signals that meet the requirements; the power conversion module adopts an asymmetric half-bridge topology to convert the DC bus voltage into adjustable excitation current for each phase winding; the status monitoring submodule collects the bus voltage, phase current, and switching transistor temperature signals of the power conversion module in real time.

[0028] The optimized PWM drive module connects to the core controller of the control layer via a GPIO interface, receiving current correction commands and protection trigger signals output by the controller. The six PWM outputs of the drive module are connected to the IGBT gates of the power conversion module via drive optocouplers, outputting isolated drive signals. The DC input of the power conversion module is connected to the DC bus power supply via a fuse, and the AC output is connected to the stator winding of the switched reluctance motor via a cable to achieve current drive. The voltage and current acquisition terminals of the status monitoring submodule are connected to the DC bus and the phase current loop via voltage divider resistors and current sampling resistors, respectively. The temperature acquisition terminal is mounted on the IGBT housing via a thermistor. The acquired status signals are conditioned and fed back to the safety protection decision module of the control layer via an ADC interface, forming a closed loop of the execution layer status.

[0029] The control method includes the following steps: Step 1: System initialization.

[0030] 1.1 After the control system is powered on, the power supply module outputs a stable voltage. The DSP controller sequentially queries the status registers of the sensing layer sensor, the execution layer driver module, and the power conversion module through the GPIO port to determine whether each hardware module is normal. If there is an abnormality, an alarm signal is sent to the host computer via UART and the system is stopped; if it is normal, the system enters the parameter configuration stage.

[0031] 1.2 The DSP controller configures the core parameters sequentially through software code. The specific order is as follows: first, set the control cycle and interrupt triggering mode; then, configure the initial parameters of the fuzzy PID controller; next, set the torque error threshold, filter window size, and power converter protection threshold; and finally, configure the sensor sampling frequency.

[0032] 1.3 Load the preset switched reluctance motor flux-current-position characteristic data table into the DSP's on-chip RAM via the SPI bus to establish a data index table for easy subsequent quick lookup; at the same time, initialize the data buffer to store the acquired data and processing results of subsequent steps.

[0033] 1.4 After initialization, the DSP controller sends a ready signal to the host computer via UART, and the system enters standby mode, waiting to receive the target torque command; at this time, the sensing layer sensor starts preheating and begins to output the initial signal.

[0034] Step 2: Parameter Acquisition and Operating Condition Identification 2.1 After the system receives the target torque command from the host computer, the DSP controller triggers a timer interrupt, and the interrupt service routine starts the parameter acquisition process.

[0035] 2.2 The photoelectric encoder in the sensing layer outputs rotor position pulse signals at a set frequency and transmits them to the signal preprocessing module through differential signal lines; the Hall current sensor synchronously acquires analog signals of the stator current of each phase and transmits them to the preprocessing module through shielded signal lines; during the acquisition process, the DSP controller monitors the acquisition status in real time through the SPI bus to ensure the integrity of signal transmission.

[0036] 2.3 The preprocessing module first performs moving average filtering on the position pulse signal to eliminate high-frequency noise, and then optimizes the signal smoothness through Kalman filtering to finally output a precise rotor position angle. The current analog signal is first corrected for zero-point drift by subtracting the static zero-point voltage, and then the amplitude is calibrated to 0-3.3V through the signal conditioning circuit. It is then converted into a 12-bit digital signal by the ADC, and finally the interference is eliminated through composite filtering to output a precise phase current value.

[0037] 2.4 The operating condition identification submodule reads the preprocessed rotor position and phase current signals from the data buffer, calculates the real-time speed using the position signal (speed = position change / control cycle), and combines this with preset operating condition classification thresholds: speed less than or equal to 500 r / min in low-speed conditions, and greater than 500 r / min in high-speed conditions; load less than or equal to 10 N·m in light-load conditions, and greater than 10 N·m in heavy-load conditions. It then determines the current operating condition type as low-speed light-load / heavy-load, high-speed light-load / heavy-load, or load abrupt transition. If the load change between two adjacent control cycles is greater than 5 N·m, it is classified as a load abrupt transition. The operating condition identification result is stored in the data buffer, and an interrupt signal is simultaneously sent to the torque command planning module.

[0038] Step 3: Torque Command Planning and Allocation 3.1 The torque command planning module reads the target torque command and operating condition identification results issued by the host computer from the data buffer. If it is a sudden load change transition condition, the first-order inertial filtering algorithm is used to smooth the target torque to eliminate the torque change impact and avoid torque pulsation caused by sudden current change. If it is a steady-state condition, the original target torque command is used directly.

[0039] 3.2. Based on the rotor position angle, divide the conducting phase region and the commutation transition region. According to the initial value of the torque distribution coefficient configured in step 1, determine the initial torque distribution weight of each phase in combination with the current speed.

[0040] 3.3 The fuzzy PID adaptive torque allocation module reads the real-time torque error (initially the difference between the target torque and the preset initial torque) and the speed change rate (the speed difference calculated in step 2 / control cycle) from the data buffer. The real-time torque error is initially the difference between the target torque and the preset initial torque, and the speed change rate is the speed difference calculated in step 2 / control cycle. Both are used as fuzzy inputs. Through 5×5 preset fuzzy rules (such as a large positive torque error, a small positive speed change rate, and a corresponding increase of 0.2 in proportional gain Kp, 0.02 in integral gain Ki, and 0.05 in derivative gain Kd), the PID parameter correction is calculated using the Mamdani inference method. Kp, Ki, and Kd are adjusted online. Then, based on the adjusted PID parameters, the torque allocation weight of each phase is dynamically optimized, the target torque value of each phase is output, and stored in the data buffer.

[0041] Step 4: Torque Observation and Error Compensation 4.1 The improved torque observation and error compensation module reads the preprocessed phase current and rotor position signals from the data buffer, and obtains the real-time flux linkage value by looking up the flux linkage-current-position characteristic data table in the on-chip RAM using a lookup table interpolation method; then, it applies the torque formula of the switched reluctance motor... Where i is the phase current, L is the inductance, and θ is the rotor position, the initial torque observation value is derived by combining the relationship between flux linkage and inductance ψ=∫Ldi.

[0042] 4.2. An extended Kalman filter algorithm is introduced to optimize the initial torque observations, treating the change in the motor's nonlinear inductance as observation noise, and establishing the observation equation. Where X is the state vector, A is the state matrix, B is the control matrix, u is the input current, w is the noise, and k is the observation time. Through a prediction-update iterative process, the optimized real-time torque observation value is output.

[0043] 4.3 Calculate the difference (torque error) between the optimized real-time torque observation value and the target torque value of each phase output in step 3. If the error is less than or equal to the torque error threshold (0.5 N·m), the current parameters are maintained. If the error is greater than the threshold, the torque observation value is dynamically corrected through the error compensation module (correction amount = error × compensation coefficient 0.1). At the same time, the torque error is input to the fuzzy PID controller. The controller calculates the stator current correction command for each phase based on the adjusted Kp, Ki, and Kd parameters and stores it in the data buffer.

[0044] Step 5: Drive Control and Safety Monitoring 5.1 The optimized PWM drive module of the execution layer reads the current correction instructions for each phase from the data buffer, adopts the improved SVPWM modulation algorithm, calculates the action time of the voltage vector of each phase according to the current instructions, and the modulation algorithm includes converting the three-phase current into two-phase stationary coordinate system current through Clark transformation, and then converting it into synchronous rotating coordinate system current through Park transformation. The voltage vector amplitude and angle are calculated to generate 6 complementary PWM drive signals. The drive signals are enhanced with anti-interference capability through isolation optocouplers.

[0045] 5.2 The PWM drive signal is transmitted to the gate of the IGBT in the power conversion module to control the IGBT's turn-on and turn-off. The power conversion module converts the DC bus voltage into an adjustable excitation current for each phase stator winding. The current amplitude is determined by the PWM duty cycle, where duty cycle = current correction command / rated current. The current is transmitted to the stator winding of the switched reluctance motor through the cable, generating electromagnetic torque to drive the rotor to rotate.

[0046] 5.3 The safety protection decision module reads the bus voltage, phase current and switching transistor temperature signals of the power conversion module from the data buffer in real time. If the bus voltage is over-voltage, the phase current is over-current or the switching transistor temperature is >85℃, the module immediately outputs a protection trigger signal to the PWM drive module, cuts off the corresponding IGBT drive signal, and sends an alarm signal to the host computer via UART. If the monitored parameters are normal, the module continues to output drive signals.

[0047] Step 6: Closed-loop feedback adjustment.

[0048] 6.1 After completing one drive control cycle, the sensing layer sensors continue to collect rotor position and phase current signals for the next control cycle at a set frequency, repeat the preprocessing process in step 2, and update the operating parameters in the data buffer; at the same time, the improved torque observation and error compensation module updates the real-time torque observation value and calculates the new torque error.

[0049] 6.2 Repeat steps 2 to 5 with a control cycle of 100μs, continuously optimizing torque distribution weight, current correction command and PWM drive signal through closed-loop feedback; if the host computer issues a new target torque command, the process is re-executed starting from the command smoothing process in step 3; if a stop command or fault alarm is detected, the loop is terminated, the drive signal is cut off, and the system enters the stop state.

[0050] Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort should fall within the scope of protection of the present invention.

Claims

1. A method for controlling the torque of a switched reluctance motor, characterized in that, Includes the following steps: Step 1: After the system is powered on, it completes hardware self-test, core parameter configuration, feature data table loading, and standby readiness. Step 2: Collect rotor position pulse signals and stator current analog signals of each phase according to the set cycle, and identify the operating conditions after preprocessing; Step 3: Smooth the target torque command and dynamically allocate the torque weight of each phase based on the operating conditions and torque error; Step 4: Obtain the initial torque observation value based on the rotor position signal and phase current signal, optimize the output real-time torque observation value, calculate the error and generate the current correction command; Step 5: Convert the current correction command into a PWM drive signal to drive the motor and monitor the safety status in real time; Step 6: Iterate through steps 2 to 5 to achieve closed-loop feedback regulation.

2. The method for controlling the torque of a switched reluctance motor according to claim 1, characterized in that, In step 2, the preprocessing includes: performing moving average filtering on the position pulse signal to eliminate high-frequency noise, optimizing signal smoothness through Kalman filtering, and outputting the rotor position angle; performing zero-point drift correction on the current analog signal, subtracting the static zero-point voltage, calibrating the amplitude to 0-3.3V through the signal conditioning circuit, converting it into a 12-bit digital signal through ADC, eliminating interference through composite filtering, and outputting the phase current value.

3. The method for controlling the torque of a switched reluctance motor according to claim 1, characterized in that, The operating condition identification method in step 2 is as follows: calculate the real-time load based on the preprocessed speed and current signals, and classify the steady-state operating condition type according to the speed and load size; determine whether it is a sudden load transition condition by monitoring the load change in adjacent control cycles.

4. The method for controlling the torque of a switched reluctance motor according to claim 1, characterized in that, Step 3, torque weight allocation, includes: dividing the conducting phase region and commutation transition region based on the rotor position angle, and determining the initial torque allocation weight of each phase; the fuzzy PID adaptive torque allocation module reads the real-time torque error and speed change rate from the data buffer, calculates the PID parameter correction amount and adjusts the PID parameters to dynamically optimize the torque allocation weight of each phase.

5. The method for controlling the torque of a switched reluctance motor according to claim 4, characterized in that, The calculation of PID parameter correction includes: using real-time torque error and speed change rate, through a preset 5×5 fuzzy rules, including a large positive torque error, a small positive speed change rate, corresponding to an increase of 0.2 in proportional gain, an increase of 0.02 in integral gain, and an increase of 0.05 in derivative gain, and calculating using the Mamdani inference method.

6. The method for controlling the torque of a switched reluctance motor according to claim 1, characterized in that, In step 4, the preprocessed phase current and rotor position signals are read, and the flux linkage-current-position characteristic data table in the on-chip RAM is looked up using the lookup table interpolation method to obtain the real-time flux linkage value. The initial torque observation value is derived by combining the torque formula of the switched reluctance motor, and the extended Kalman filter algorithm is introduced to optimize the initial torque observation value, and the optimized real-time torque observation value is output. The difference between the optimized real-time torque observation value and the target torque value of each phase is calculated, the torque observation value is dynamically corrected, and a current correction command is generated.

7. The method for controlling the torque of a switched reluctance motor according to claim 1, characterized in that, In step 5: Read the current correction command for each phase, use the improved SVPWM modulation algorithm, calculate the action time of the voltage vector of each phase according to the current command. The modulation algorithm includes converting the three-phase current into a two-phase stationary coordinate system current through Clark transformation, and then converting it into a synchronous rotating coordinate system current through Park transformation. Calculate the voltage vector amplitude and angle, and generate the PWM drive signal.

8. The method for controlling the torque of a switched reluctance motor according to claim 1, characterized in that, The closed-loop feedback adjustment in step 6 is iterated at intervals set by the control cycle. If the host computer issues a new target torque command, the process is restarted from the command smoothing process in step 3. If a stop command or fault alarm is detected, the loop is terminated, the drive signal is cut off, and the system enters a stop state.

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