Reconfigurable electric motor control system and method based on eso

Abstract

The application discloses a hub motor-oriented ESO-based hub motor system design method, and belongs to the technical field of longitudinal dynamics control of multi-axle vehicle multi-wheel independent driving. The method comprises the following steps: 1) a model of the hub motor system is established based on a q-d reference frame; 2) the system is transformed into a state space model through the established model; 3) an extended state observer (ESO) is designed to reconstruct the hub motor system; and 4) a current constraint controller is designed, and a tracking differentiator is designed to deal with the overcurrent problem of hub motor speed regulation in consideration of overcurrent and total disturbance, i.e. measurement noise, parameter uncertainty, external load torque disturbance and the like. The hub motor system is controlled by using a composite current constraint control method based on a non-cascaded single-loop speed control structure. Compared with a conventional PID controller, the proposed composite controller has better speed regulation performance and stronger anti-interference ability, and can meet the current constraint condition.

Description

Technical Field

[0001] This invention belongs to the field of system reconfiguration technology for hub motors, specifically a reconfigurable hub motor control system and method based on ESO. Background Technology

[0002] To ensure the stable and reliable operation of hub motors, research on motor control technology is necessary, with a focus on control strategies under various operating conditions. In practical industrial control systems, especially in high-performance speed control applications, current sensors play a crucial role in real-time current signal acquisition. However, under harsh environmental conditions, such as high and low temperatures or humidity, current sensors may malfunction, leading to decreased accuracy or even damage. This directly affects the motor's speed control performance, operational stability, and controllability, ultimately endangering the safety of the vehicle driver.

[0003] Therefore, research on fault control of in-wheel motor current sensors is crucial. The goal of this research is to develop reliable control methods and strategies to address situations where the current sensor fails. This research ensures that motor operation can still be effectively monitored and controlled even when the current sensor fails. This will improve the fault tolerance and robustness of the entire in-wheel motor system, guaranteeing stable operation of the motor in uncertain or harsh environments while reducing potential risks and hazards.

[0004] Traditional PID controllers do not consider current constraint mechanisms and choose conservative parameters to constrain the current, which may sacrifice the dynamic performance of the entire control system. Therefore, many modern control methods have been gradually applied to high-precision hub motors, but due to uncertainties and disturbances, the cost function is difficult to model. To address this issue, a penalty mechanism for state constraints in the control behavior is progressively advanced by constructing a nonlinear function of the state. Applying a current-constrained PID controller to the hub motor demonstrates satisfactory dynamic and current-limiting performance. Unfortunately, the mismatch disturbance problem in the current loop remains unresolved.

[0005] In recent years, various disturbance estimation methods have been increasingly applied to mitigate mismatch and matched disturbances in hub motors, such as the Disturbance Observer (DOB), High Gain Observer (HGO), Generalized Proportional-Integral Observer (GPIO), and Extended State Observer (ESO). ESO is a model-independent observer with advantages such as fast convergence speed and high convergence accuracy; therefore, ESO-based controllers have been widely used. In conclusion, reconstructing the hub motor system using ESO to consider the state constraints and anti-interference capabilities of the hub motor is meaningful. Summary of the Invention

[0006] In view of the above-mentioned problems in the prior art, the purpose of this invention is to provide a reconfigurable hub motor control system and method based on ESO, which effectively solves the problem of bidirectional interaction between estimation signals and uses the output signal to implicitly estimate sensor faults.

[0007] The design method of the reconfigurable hub motor control system based on ESO of this invention includes the following specific steps:

[0008] Step 1: Modeling the hub motor system.

[0009] In the dq reference frame, the hub motor system is modeled as follows:

[0010]

[0011] in, and They are respectively and Stator voltage; and

[0012] The state currents are defined as follows: and ; Time constant; coefficient ,

[0013] and They represent and Inductance of the stator windings; motor parameters and These represent the stator resistance, permanent magnet flux, mechanical angular acceleration, and number of pole pairs of the motor, respectively. and These are total inertia, total friction coefficient, and load torque, respectively.

[0014] Wherein, given electromagnetic torque .

[0015] Step 2: Construct a state-space model of the hub motor system and transform matched and mismatched disturbances into uniformly matched disturbances.

[0016] Step 3: Design a third-order linear ESO to estimate the matching disturbance and compensate it through a feedforward channel. Based on the designed ESO, design a tracking differentiator that balances overshoot and fast response. Further reconstruct the composite current constraint controller with tracking differentiator for the hub motor system.

[0017] The advantages of this invention are:

[0018] 1. The present invention relates to a reconfigurable hub motor control system and method based on ESO, which solves the overcurrent problem by designing a tracking differentiator in the controller, and resolves the contradiction between overshoot, fast response and initial value of manipulated variable.

[0019] 2. The present invention relates to a reconfigurable hub motor control system and method based on ESO. In the reconfigured hub motor system, a composite current constraint controller with a tracking differentiator is designed. Compared with the traditional PID controller, it not only has better speed regulation performance, but also stronger anti-interference ability and can meet the current constraint conditions. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating the design method of the reconfigurable hub motor control system based on ESO according to the present invention. Detailed Implementation

[0021] The present invention will now be described in further detail with reference to the accompanying drawings.

[0022] This invention relates to a design method for an ESO-based reconfigurable hub motor system, the specific steps of which are as follows:

[0023] Step 1: Modeling the hub motor system.

[0024] In the dq reference frame, the hub motor system is modeled as follows:

[0025] (1)

[0026] in, and They are respectively and The stator voltage. and The state currents are defined as follows: and . It is a time constant. Furthermore, the coefficients... , and They represent and The inductance of the stator windings. Motor parameters. and These represent the stator resistance, permanent magnet flux, mechanical angular acceleration, and number of pole pairs of the motor, respectively.

[0027] The dynamic mechanical model between the load and the hub motor system can be represented as:

[0028] (2)

[0029] in, and These are the total inertia, total friction coefficient, and load torque, respectively. Based on typical hub motor parameters, the electromagnetic torque is given... To eliminate potential coupling issues, set... The control strategy. Using equation (2), the hub motor system model is established as follows:

[0030] (3)

[0031] Step 2: Construct the state-space model of the hub motor system.

[0032] To transform mismatched and matched interference into perfectly matched interference, variables are defined. and A novel state-space model for velocity tracking is designed. , The hub motor system model (3) can be constructed in the following form:

[0033] (4) (5)

[0034] in, , , Total disturbance Replacement, including disturbances in the hub motor system caused by current fluctuations and load torque. and and internal disturbances of the hub motor system .in, and Each satisfies and .

[0035] Due to the characteristics of hub motors, even with very short intervals, load jumps can be interpreted as ramp functions. Therefore, the state variables and total disturbance of the hub motor system satisfy the differential boundedness condition. Parameters The system uncertainty that represents the modeling error.

[0036] Will Defined as ,but

[0037] (6)

[0038] According to (6), the state-space model of the hub motor system can be obtained as follows:

[0039] (7)

[0040] Rewrite equation (7) as a second-order system:

[0041] (8)

[0042] in, , .

[0043] Step 3: Reconstruct the hub motor system based on the Extended Observer (ESO).

[0044] To address the issue of a system being unable to operate normally due to a hub motor failure, this invention proposes a hub motor system reconfiguration strategy based on ESO (Electronic Stability Evaluation) to estimate the state and total disturbance of the hub motor system.

[0045] Through equation (8), the total disturbance It should be represented as a new state variable, which can be represented as Its derivative is defined as Then the state-space model of the hub motor system can be reconstructed as follows:

[0046] (9)

[0047] Based on equation (9), the following third-order ESO is established:

[0048] (10)

[0049] in and They are respectively and The estimated value, observer coefficient and This is the observation gain value. According to (9) and (10), the observation error value... Defined as .

[0050] The observer error can then be modeled as:

[0051] (11)

[0052] in, These are the velocity estimation error, velocity difference estimation error, and disturbance estimation error, respectively.

[0053] The ESO designed using the above method has global convergence because the characteristic polynomial of the error coefficient matrix satisfies the Hurwitz stability condition, and the system's poles can remain in the left half of the complex plane, i.e., the error variable. It can gradually converge to zero.

[0054] Step 3.1: Design a current constraint controller based on ESO.

[0055] According to equation (8), zero steady-state error can be achieved using a simple proportional-derivative controller. However, when speed and current form a closed-loop system, The current represents the state of the hub motor system, not a control variable. Therefore, the control law for the composite current-constrained controller with a tracking differentiator for the ESO-reconstructed hub motor system, based on the aforementioned design, is as follows:

[0056] (12)

[0057] in, For the desired speed, and This is expressed as the derivative of the desired velocity. Proportional-derivative controller coefficients. These are adjustable parameters for the feedback controller. The boundary values ​​of the current constraint are given, while the parameters are... This indicates the weight of the current constraint.

[0058] Step 3.2: Design a tracking differentiator based on ESO to balance overshoot and fast response. When a fault occurs in the hub motor system, it will cause large current fluctuations, making the instantaneous...

[0059] The current becomes too large and violates the constraints. Therefore, a tracking differentiator is designed to prevent excessive current from damaging the motor when the hub motor system malfunctions. In addition, the tracking differentiator can also suppress disturbances by extracting the difference in speed signals.

[0060] The tracking differentiator is designed as follows:

[0061] (13)

[0062] in, respectively the expected speed The tracking signal and its derivative. For the desired speed The velocity factor.

[0063] Therefore, the final constructed composite current constraint controller based on ESO with a tracking differentiator is expressed as follows:

[0064] (14)

[0065] According to equation (14), the actual input voltage of the hub motor is... It can be designed in the following form:

[0066] (15)

[0067] The hub motor system reconstructed using the above method, compared with existing technologies, utilizes a composite current constraint controller with a tracking differentiator to address overcurrent issues and resolve the conflict between overshoot, fast response, and the initial value of the manipulated variable. Compared with traditional PID controllers, the proposed composite controller not only has better speed regulation performance but also stronger anti-interference capabilities and can meet current constraint conditions.

Claims

1. A design method for an ESO-based reconfigurable hub motor system for hub motors, characterized by: The steps are designed as follows: Step 1: Modeling the hub motor system; In the dq reference frame, the hub motor system is modeled as follows: in, and They are respectively and Stator voltage; and The state currents are defined as follows: and ; Time constant; coefficient , and They represent and Inductance of the stator windings; motor parameters and These represent the stator resistance, permanent magnet flux, mechanical angular acceleration, and number of pole pairs of the motor, respectively. and These are total inertia, total friction coefficient, and load torque, respectively. Wherein, given electromagnetic torque ; Step 2: Construct the state-space model of the hub motor system, and transform matched and mismatched disturbances into uniformly matched disturbances; Step 3: Design a third-order linear ESO to estimate the matching disturbance and compensate it through a feedforward channel. Based on the designed ESO, design a tracking differentiator that balances overshoot and fast response. Further reconstruct the composite current constraint controller of the hub motor system with the tracking differentiator. Specifically, the total disturbance of the hub motor system is... Represented as a new state variable, , The derivative is defined as The state-space model of the hub motor system is then reconstructed as follows: In the formula, ; To define variables, ; Subsequently, a third-order ESO is established as follows: in, and They are respectively and The estimated value, observer coefficient and It is the observation gain value; according to the above formula, the observation error value is... Defined as ; The observer error is then modeled as: in, These are velocity estimation error, velocity difference estimation error, and disturbance estimation error, respectively. Based on the aforementioned design, a composite current-constrained controller with a tracking differentiator is used to reconfigure the ESO hub motor system. The control law is as follows: in, For the desired speed, The proportional-derivative control coefficient is expressed as the derivative of the desired speed. These are adjustable parameters for the feedback controller; This represents the boundary value of the current constraint. Indicates the weight of the current constraint; Based on the aforementioned design, an ESO design is used to balance overshoot and fast response tracking differentiator. as follows: in, respectively the expected speed The tracking signal and its derivative; For the desired speed The velocity factor; Therefore, the final constructed composite current constraint controller with a tracking differentiator is expressed as follows: According to the above formula, the actual input voltage of the hub motor is... The design is as follows: 。 2. The design method for an ESO-based reconfigurable hub motor system for hub motors as described in claim 1, characterized in that: In step 1, State current This eliminates the coupling phenomenon.

3. The design method for an ESO-based reconfigurable hub motor system for hub motors as described in claim 1, characterized in that: The specific method for step 2 is as follows: Define variables and , , The hub motor system model from step 1 is constructed as follows: in, The total disturbance includes the in-wheel motor system caused by current fluctuations and load torque. The disturbance and and internal disturbances of the hub motor system ; but , , , , and Each satisfies and ; This represents the system uncertainty of modeling error; definition ,but Furthermore, the state-space model of the hub motor system is obtained as follows: And rewritten as a second-order system: in, , .

Images