A method for estimating position and speed of a permanent magnet synchronous motor and a related device

Abstract

The application discloses a permanent magnet synchronous motor position and speed estimation method and related equipment thereof, and the method comprises the following steps: in response to a request for position sensorless control of a permanent magnet synchronous motor, obtaining operating electrical data and control configuration parameters, establishing a full fractional order sliding mode observer basic model, determining position and speed observation errors according to output observation data and real-time state data, configuring parameters of a sign function of a sliding mode control term in the full fractional order sliding mode observer basic model, determining a preliminary position estimation value, and then substituting the preliminary position estimation value into a fractional order PLL control law state evolution equation to obtain a position and speed estimation value. As can be seen, by adopting the full fractional order sliding mode observer, the flexible characteristics of the fractional order operator are used to suppress chattering and reduce noise influence; the sliding mode control parameters are adaptively adjusted according to the observation errors to accelerate error convergence; and the position and speed estimation is precisely coupled through the fractional order PLL, so that the observation accuracy, convergence speed and full working condition stability are comprehensively improved.

Description

Technical Field

[0001] This application relates to the field of motor control technology, and more specifically, to a method for estimating the position and speed of a permanent magnet synchronous motor and related equipment. Background Technology

[0002] Permanent magnet synchronous motors are widely used in industrial servo systems, new energy drives, and other fields. Sensorless control can eliminate mechanical sensors, reduce costs, and improve reliability, and has become the mainstream technology. The accurate estimation of position and speed is its core key.

[0003] Existing position-speed estimation methods mostly employ integer-order sliding mode observers combined with PLL schemes. However, due to the rigidity limitations of integer-order operators, high-frequency chattering at low speeds easily amplifies noise, resulting in poor observation accuracy. Some improvements only introduce fractional-order operators locally, but their convergence speed and disturbance rejection capabilities are insufficient. Under highly dynamic operating conditions (such as sudden speed changes and load fluctuations), the response speed of the integer-order architecture is difficult to match the dynamic characteristics of the motor, leading to observation lag.

[0004] Improving the accuracy and convergence speed of position and speed estimation for permanent magnet synchronous motors, and enhancing the stability of observation under all operating conditions, are issues that need attention. Summary of the Invention

[0005] In view of the above problems, this application provides a method and related equipment for estimating the position and speed of a permanent magnet synchronous motor, so as to improve the accuracy and convergence speed of the position and speed estimation of the permanent magnet synchronous motor and enhance the stability of observation under all operating conditions.

[0006] To achieve the above objectives, the following specific solutions are proposed:

[0007] A method for estimating the position and speed of a permanent magnet synchronous motor, comprising:

[0008] In response to a sensorless control request for a permanent magnet synchronous motor, the system acquires the operating electrical data and control configuration parameters of the permanent magnet synchronous motor.

[0009] Based on the aforementioned operational electrical data and control configuration parameters, observation modeling is performed to obtain the basic model of the full fractional sliding mode observer;

[0010] Based on the output observation data of the full fractional sliding mode observer basic model and the state data of the permanent magnet synchronous motor, the position observation error and speed observation error of the permanent magnet synchronous motor are determined.

[0011] Based on the position observation error and the rotational speed observation error, the parameters of the sign function of the sliding mode control term in the full fractional sliding mode observer basic model are configured to obtain the fully configured full fractional sliding mode observer model, and the preliminary position estimate output by the full fractional sliding mode observer model is obtained.

[0012] A state evolution equation for a fractional-order PLL control law is constructed, and based on the preliminary position estimate and the state evolution equation, the position estimate and speed estimate of the permanent magnet synchronous motor are determined.

[0013] Optionally, the operating electrical data includes stator three-phase voltage and stator three-phase current;

[0014] Based on the aforementioned operational electrical data and control configuration parameters, observation modeling is performed to obtain the basic model of the full fractional-order sliding mode observer, including:

[0015] The three-phase stator voltage is converted into two-phase voltage components by electrical quantity conversion.

[0016] The three-phase stator current is converted into electrical quantities to obtain two-phase current components;

[0017] Based on the two-phase voltage components and the two-phase current components, the stator voltage equation and current observation equation are constructed.

[0018] A current observation error is constructed, and a fractional-order sliding surface is constructed based on the control configuration parameters and the current observation error;

[0019] A sliding mode control term is constructed using the current observation error, and a state evolution equation is constructed based on the sliding mode control term and the current observation equation to obtain the basic model of the full fractional sliding mode observer.

[0020] Optionally, based on the output observation data of the full fractional-order sliding mode observer basic model and the state data of the permanent magnet synchronous motor, the position observation error and speed observation error of the permanent magnet synchronous motor are determined, including:

[0021] Extract the back electromotive force observation value of the basic model of the full fractional sliding mode observer;

[0022] The first estimated value of the position is calculated using the observed back electromotive force, and the first estimated value of the rotational speed is obtained by differentiating the first estimated value of the position.

[0023] Determine the position observation error between the first estimated position and the actual position of the permanent magnet synchronous motor, and the speed observation error between the first estimated speed and the actual speed of the permanent magnet synchronous motor.

[0024] Optionally, based on the position observation error and the rotational speed observation error, the parameters of the sign function of the sliding mode control term in the full fractional sliding mode observer basic model are configured to obtain the fully configured full fractional sliding mode observer model, including:

[0025] The gain coefficient of the sliding control term in the basic model of the full fractional sliding observer is adjusted by the following formula:

[0026]

[0027] in, The gain coefficient of the sliding mode control term. This is the initial value of the gain. For gain adjustment step size, The absolute value of the position observation error. This is the absolute value of the observed rotational speed error;

[0028] The sliding mode control term is updated using the gain coefficient to obtain a fully configured full fractional sliding mode observer model.

[0029] Optionally, the state evolution equation of the fractional-order PLL control law is:

[0030]

[0031] in, For fractional differential operators, For the order of fractional differential operators, This is the estimated position value of the permanent magnet synchronous motor. This is the estimated speed of the permanent magnet synchronous motor. This is the PLL scaling factor. For PLL integral coefficients, For the state evolution equation Fractional integral operator;

[0032] Based on the preliminary position estimate and the state evolution equation, the position estimate and speed estimate of the permanent magnet synchronous motor are determined, including:

[0033] Substituting the preliminary position estimate into the state evolution equation, the position observation error drives the PLL state evolution to obtain the position estimate and speed estimate of the permanent magnet synchronous motor.

[0034] Optionally, the fractional-order sliding surface can be in the following form:

[0035]

[0036] in, This represents the α phase after Clark transformation. This represents the β phase after Clark transformation. For the α phase of the fractional-order sliding surface, For the β phase of the fractional-order sliding surface, For fractional differential operators, For the order of fractional differential operators, , This is the sliding surface adjustment coefficient. , The current observation error for phase α is... The current observation error for phase β.

[0037] Optionally, the method further includes:

[0038] Discretizing the fractional-order sliding surface yields the discretized fractional-order sliding surface as follows:

[0039]

[0040] in, For the α phase of the discretized fractional-order sliding surface, For the β phase of the discretized fractional-order sliding surface, The gain coefficient of the sliding mode control term. This is the sampling step size.

[0041] A device for estimating the position and speed of a permanent magnet synchronous motor, comprising:

[0042] The data parameter acquisition module is used to respond to the sensorless control request of the permanent magnet synchronous motor and acquire the operating electrical data and control configuration parameters of the permanent magnet synchronous motor.

[0043] The model building module is used to perform observation modeling based on the operating electrical data and the control configuration parameters to obtain the basic model of the full fractional sliding mode observer;

[0044] The observation error determination module is used to determine the position observation error and speed observation error of the permanent magnet synchronous motor based on the output observation data of the full fractional sliding mode observer basic model and the state data of the permanent magnet synchronous motor.

[0045] The model configuration module is used to configure the parameters of the sign function of the sliding control term in the basic model of the full fractional sliding mode observer based on the position observation error and the rotational speed observation error, so as to obtain the fully configured full fractional sliding mode observer model and obtain the preliminary position estimate output by the full fractional sliding mode observer model.

[0046] The estimation output module is used to construct the state evolution equation of the fractional-order PLL control law, and based on the preliminary position estimate and the state evolution equation, determine the position estimate and speed estimate of the permanent magnet synchronous motor.

[0047] Optionally, the operating electrical data includes stator three-phase voltage and stator three-phase current;

[0048] The model building module includes:

[0049] The voltage component conversion module is used to convert the three-phase stator voltage into electrical quantities to obtain two-phase voltage components;

[0050] The current component conversion module is used to convert the three-phase stator current into electrical quantities to obtain two-phase current components;

[0051] The equation construction module is used to construct the stator voltage equation and the current observation equation based on the two-phase voltage components and the two-phase current components;

[0052] A fractional-order sliding surface construction module is used to construct the current observation error and, based on the control configuration parameters and the current observation error, construct a fractional-order sliding surface.

[0053] The state evolution equation construction module is used to construct a sliding mode control term through the current observation error, and based on the sliding mode control term and the current observation equation, construct a state evolution equation to obtain the basic model of the full fractional sliding mode observer;

[0054] Optionally, the observation error determination module includes:

[0055] The back electromotive force observation extraction module is used to extract the back electromotive force observations of the basic model of the full fractional sliding mode observer.

[0056] The position and rotational speed first estimate calculation module is used to calculate the first estimate of position using the back electromotive force observation value, and differentiate the first estimate of position to obtain the first estimate of rotational speed;

[0057] An error determination module is used to determine the position observation error between the first estimated position value and the actual position of the permanent magnet synchronous motor, and the speed observation error between the first estimated speed value and the actual speed of the permanent magnet synchronous motor.

[0058] Optionally, the model configuration module includes:

[0059] The gain coefficient adjustment module is used to adjust the gain coefficient of the sliding control term in the basic model of the full fractional sliding mode observer using the following formula:

[0060]

[0061] in, The gain coefficient of the sliding mode control term. This is the initial value of the gain. For gain adjustment step size, The absolute value of the position observation error. This is the absolute value of the observed rotational speed error;

[0062] The sliding mode control term update module is used to update the sliding mode control term using the gain coefficient to obtain a fully configured full fractional sliding mode observer model and to obtain the preliminary position estimate output by the full fractional sliding mode observer model.

[0063] Optionally, the state evolution equation of the fractional-order PLL control law is:

[0064]

[0065] in, For fractional differential operators, For the order of fractional differential operators, This is the estimated position value of the permanent magnet synchronous motor. This is the estimated speed of the permanent magnet synchronous motor. This is the PLL scaling factor. For PLL integral coefficients, For the state evolution equation Fractional integral operator;

[0066] The estimated value output module includes:

[0067] The estimation output submodule is used to substitute the preliminary position estimate into the state evolution equation, and drive the PLL state evolution with the position observation error to obtain the position estimate and speed estimate of the permanent magnet synchronous motor.

[0068] Optionally, the fractional-order sliding surface can be in the following form:

[0069]

[0070] in, This represents the α phase after Clark transformation. This represents the β phase after Clark transformation. For the α phase of the fractional-order sliding surface, For the β phase of the fractional-order sliding surface, For fractional differential operators, For the order of fractional differential operators, , This is the sliding surface adjustment coefficient. , The current observation error for phase α is... The current observation error for phase β.

[0071] Optionally, the device may also include:

[0072] The fractional-order sliding surface discretization module is used to discretize the fractional-order sliding surface, resulting in the following discretized fractional-order sliding surface:

[0073]

[0074] in, For the α phase of the discretized fractional-order sliding surface, For the β phase of the discretized fractional-order sliding surface, The gain coefficient of the sliding mode control term. This is the sampling step size.

[0075] A device for estimating the position and speed of a permanent magnet synchronous motor, comprising a memory and a processor;

[0076] The memory is used to store programs;

[0077] The processor is used to execute the program to implement the various steps of the method for estimating the position and speed of a permanent magnet synchronous motor as described above.

[0078] A storage medium storing a computer program, which, when executed by a processor, implements the steps of the method for estimating the position and speed of a permanent magnet synchronous motor as described above.

[0079] By employing the above technical solution, this application obtains the operating electrical data and control configuration parameters of a permanent magnet synchronous motor (PMSM) in response to a sensorless control request. Based on the operating electrical data and control configuration parameters, observation modeling is performed to obtain a basic model of a full fractional sliding mode observer. According to the output observation data of the full fractional sliding mode observer basic model and the state data of the PMSM, the position observation error and speed observation error of the PMSM are determined. Based on the position observation error and speed observation error, the parameters of the sign function of the sliding mode control term in the full fractional sliding mode observer basic model are configured to obtain a fully configured full fractional sliding mode observer model. The preliminary position estimate output by the full fractional sliding mode observer model is obtained. Based on the preliminary position estimate and the state evolution equation of the fractional PLL control law, the position and speed estimates are determined. Therefore, by adopting a full fractional sliding mode observer, the flexible characteristics of fractional operators are used to suppress chattering and reduce the impact of noise; the sliding mode control parameters are adaptively adjusted with the observation error to accelerate error convergence; and the position and speed estimation are precisely coupled through fractional PLL, thereby comprehensively improving the observation accuracy, convergence speed and stability under all operating conditions. Attached Figure Description

[0080] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0081] Figure 1 A schematic diagram of a process for estimating the position and speed of a permanent magnet synchronous motor, provided in an embodiment of this application;

[0082] Figure 2 A schematic diagram illustrating the process of constructing a basic model of a fully fractional sliding mode observer, provided for an embodiment of this application;

[0083] Figure 3 A schematic diagram of a device for estimating the position and speed of a permanent magnet synchronous motor, provided in an embodiment of this application;

[0084] Figure 4 This is a schematic diagram of a device for estimating the position and speed of a permanent magnet synchronous motor, provided in an embodiment of this application. Detailed Implementation

[0085] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0086] The proposed solution can be implemented based on a terminal with data processing capabilities, such as a computer, cloud, or server.

[0087] Next, this application provides an estimation scheme for the position and speed of a permanent magnet synchronous motor. It is understood that permanent magnet synchronous motors are widely used in industrial servo and new energy drive scenarios, where sensorless control is widely adopted due to the elimination of mechanical sensors and the reduction of cost and size. However, existing integer-order sliding mode observation schemes have significant limitations:

[0088] First, the rigidity of the integer-order sliding surface amplifies the current noise at low speeds, causing severe jitter in the observed signal and affecting control accuracy.

[0089] Secondly, during highly dynamic operation (such as sudden changes in speed or load fluctuations), the response rate of the integer-order observer cannot match the dynamic characteristics of the motor, resulting in significant observation lag.

[0090] Third, parameter tuning relies on engineering debugging experience, and the observed performance fluctuates greatly under different operating conditions. Furthermore, there is a lack of theoretical proof of convergence at the fractional-order system level, making it difficult to guarantee stability under all operating conditions.

[0091] The estimation scheme for the position and speed of the permanent magnet synchronous motor in this application aims to alleviate observation chattering at low speeds by utilizing the flexible adjustment characteristics of the fractional sliding mode surface, and to improve the observation response speed under high dynamic conditions by utilizing the dynamic adaptation capability of the fractional operator. At the same time, the convergence of the observation process is proved by using the Lyapunov function of the fractional system, providing theoretical support for the stability of observation under all operating conditions.

[0092] It should be noted that the core of the full fractional-order sliding mode observer lies in constructing the sliding surface through fractional-order differential operators. The order parameter of the sliding surface determines the flexibility of the sliding surface, while the fractional-order PLL is used to correct the position observation value, so as to achieve precise coupling between the position and rotational speed observation values. This scheme drives the adjustment of the sliding mode control parameters through the observation error, so as to achieve the balance of observation performance under different working conditions.

[0093] Based on this, combined Figure 1 The method for estimating the position and speed of the permanent magnet synchronous motor in this application may include the following steps:

[0094] Step S110: Respond to the sensorless control request for the permanent magnet synchronous motor and obtain the operating electrical data and control configuration parameters of the permanent magnet synchronous motor.

[0095] Among them, the sensorless control request can represent a control command that estimates the rotor position and speed of a permanent magnet synchronous motor without the need for mechanical position sensors, relying solely on electrical signals. Its goal is to accurately acquire the rotor position and speed to support the realization of motor vector control.

[0096] Operating electrical data can be a set of parameters reflecting the electrical state of a permanent magnet synchronous motor during operation, specifically including the stator. Phase current ,stator Phase current ,stator Phase voltage ,stator Phase voltage (It can also be stator three-phase current and stator three-phase voltage, but in the subsequent step S120, it needs to be transformed into stator voltage by Clark.) Phase current ,stator Phase current ,stator Phase voltage ,stator Phase voltage Actual rotor position (Used for error calculation during the commissioning phase), actual rotor speed (Used for error calculation during the debugging phase), etc.

[0097] The control configuration parameters can be fixed or initial parameters used to build the observation model, and can specifically include the order of fractional differential operators. (satisfy Sliding surface adjustment coefficient (satisfy ), initial coefficient of sliding mode control term gain Fractional PLL scaling factor Fractional PLL integral coefficients Gain adjustment step size Sampling step size .

[0098] Step S120: Based on the operating electrical data and control configuration parameters, perform observation modeling to obtain the basic model of the full fractional sliding mode observer.

[0099] Understandably, replacing the traditional integer-order architecture with fractional-order operators endows the observer with stronger flexible adjustment capabilities, effectively suppressing high-frequency chattering and current noise amplification under low-speed conditions, and significantly improving observation accuracy. Simultaneously, the fractional-order sliding surface and error dynamic model better adapt to the wide range of dynamic characteristics of the motor, accelerating the convergence speed of observation errors. The model does not rely on the motor's fractional-order body model, retaining the strong disturbance rejection advantages of the sliding mode observer. Parameter tuning is more theoretically grounded, and it can stably adapt to complex operating conditions such as sudden speed changes and load fluctuations, providing reliable underlying support for accurate and stable position and speed observation under all operating conditions.

[0100] Specifically, the process of obtaining the basic model of the full fractional-order sliding mode observer by performing observation modeling based on operating electrical data and control configuration parameters can be found in [reference needed]. Figure 2 Specifically, it includes the following steps:

[0101] Step S121: Perform electrical quantity conversion on the three-phase stator voltage to obtain two-phase voltage components, and perform electrical quantity conversion on the three-phase stator current to obtain two-phase current components.

[0102] Specifically, based on the coordinate transformation requirements of the permanent magnet synchronous motor's vector control, Clark transformation equations can be constructed to realize the transformation from a three-phase stationary ABC coordinate system to a two-phase stationary coordinate system. The core equation for electrical quantity conversion in a coordinate system, the Clark transform, is:

[0103]

[0104] in, These are the constant amplitude transformation coefficients. The stator phase currents are in a three-phase stationary ABC coordinate system. The stator phase voltages are in the three-phase stationary ABC coordinate system. Two-phase stationary Stator current components in the coordinate system Two-phase stationary Stator voltage components in the coordinate system.

[0105] Step S122: Based on the two-phase voltage components and the two-phase current components, construct the stator voltage equation and the current observation equation.

[0106] The stator voltage equation is as follows:

[0107]

[0108] in, For stator equivalent inductance, For back electromotive force (satisfying) , , (Permanent magnet magnetic flux).

[0109] The equation for current observation is:

[0110]

[0111] in, These are the observed values ​​of phase a and phase b currents. This is the observed value of the back electromotive force.

[0112] Step S123: Construct the current observation error, and based on the control configuration parameters and the current observation error, construct a fractional-order sliding surface.

[0113] The fractional-order sliding surface takes the following form:

[0114]

[0115] in, For the α phase of a fractional-order sliding surface, For the β phase of a fractional-order sliding surface, For Caputo fractional differential operators, For the order of fractional differential operators, , This is the sliding surface adjustment coefficient. , The error in current observation for phase α is... This represents the current observation error for phase β.

[0116] Considering that commonly used digital controllers (DSPs, MCUs, FPGAs, etc.) in industrial scenarios are discrete-time systems, with their core operating mechanism being periodic interrupt execution with a fixed sampling step size, digital controllers cannot directly solve for infinite-dimensional differential operations in continuous time, resulting in fundamental differences in their operating domains. Furthermore, real-time estimation is a core prerequisite for the industrial implementation of sensorless control schemes for permanent magnet synchronous motors. Accurate rotor position signals are the core basis for Clark / Park coordinate transformation, and speed signals are the core feedback quantity for speed closed-loop control. If the position-speed estimation is not real-time, it will directly lead to inaccurate coordinate transformation, current decoupling failure, resulting in motor torque pulsation, decreased control accuracy, and reduced operating efficiency. In severe cases, it can cause the motor to lose synchronization and fail to operate normally. To meet the requirements of engineering digital controllers, the full fractional-order sliding mode observer can be discretized.

[0117] Specifically, the Grünwald-Letnikov (GL) fractional-order discretization scheme can be used to calculate the sliding surface, and the Caputo fractional derivative can be used for this purpose. Its GL discrete approximation is:

[0118]

[0119] in, The sampling step size, is the coefficient of the fractional binomial.

[0120] Therefore, the discretization form of the fractional-order sliding surface is:

[0121]

[0122] in, For the α phase of the discretized fractional-order sliding surface, For the β phase of the discretized fractional-order sliding surface, This represents the gain coefficient of the sliding mode control term. The sampling step size is defined as follows. The binomial coefficients (μ, m) in the discrete formula are only related to the fractional order μ and the historical term index m, and are independent of the motor's operating state. They can be pre-calculated and stored during controller initialization, eliminating the need for repeated calculations in each sampling period and significantly reducing real-time computation. The GL discrete format naturally supports short-memory optimization. In actual hardware implementation, a fixed-length historical data window (retaining only the most recent N sampling points) can be set based on the sampling step size and fractional order, truncating long-term historical data that has minimal impact on observation accuracy. This fixes the computational load for each sampling period to a finite number of additions and multiplications, ensuring that the computational load does not increase with runtime. This perfectly adapts to the limited computing power of the digital controller, guaranteeing that all calculations are completed within sampling periods of tens of microseconds. Therefore, this discrete equation solves the problem that continuous-time fractional sliding mode observers cannot be directly run in digital controllers, ensuring that the observer can estimate position and speed in real-time in actual hardware.

[0123] Step S124: Construct a sliding mode control term through the current observation error, and based on the sliding mode control term and the current observation equation, construct a state evolution equation to obtain the basic model of the full fractional sliding mode observer.

[0124] The sliding mode control items are as follows:

[0125]

[0126] in, This is the initial value of the sliding mode control gain. It is a symbolic function.

[0127] Furthermore, substituting the sliding mode control term into the current observation equation, we obtain the state evolution expression for the full fractional-order sliding mode observer as follows:

[0128]

[0129] Step S130: Based on the output observation data of the full fractional sliding mode observer basic model and the state data of the permanent magnet synchronous motor, determine the position observation error and speed observation error of the permanent magnet synchronous motor.

[0130] Understandably, by comparing the observer output data with the actual motor state data, accurately calculating the position and speed observation errors can provide real-time and accurate error feedback for subsequent adaptive adjustment of sliding mode control parameters. Driving parameter adjustment with actual errors avoids the operating condition adaptation deviation caused by experience-based tuning, effectively reduces steady-state estimation deviation, and improves the accuracy of position and speed observations. Simultaneously, real-time error calculation can quickly respond to dynamic changes such as sudden changes in motor speed and load fluctuations, shortening error correction lag and accelerating system convergence.

[0131] Specifically, the process of determining the position observation error and speed observation error of the permanent magnet synchronous motor based on the output observation data of the full fractional sliding mode observer basic model and the state data of the permanent magnet synchronous motor can include:

[0132] S131. Extract the back electromotive force observation value of the basic model of the full fractional sliding mode observer.

[0133] Specifically, the back electromotive force observation can be extracted from the output of the basic model of the full fractional sliding mode observer. .

[0134] S132. Calculate the first estimated value of position using the back electromotive force observation value, and differentiate the first estimated value of position to obtain the first estimated value of rotational speed.

[0135] Specifically, the first estimated value of the location is The first estimated value of the rotational speed is .

[0136] S133. Determine the position observation error between the first estimated position and the actual position of the permanent magnet synchronous motor, and the speed observation error between the first estimated speed and the actual speed of the permanent magnet synchronous motor.

[0137] Specifically, the position observation error is , The actual position of the permanent magnet synchronous motor, with a speed observation error of [missing information]. , This represents the actual speed of the permanent magnet synchronous motor.

[0138] Step S140: Based on the position observation error and rotational speed observation error, configure the parameters of the sign function of the sliding mode control term in the full fractional sliding mode observer basic model to obtain the fully configured full fractional sliding mode observer model, and obtain the preliminary position estimate output by the full fractional sliding mode observer model.

[0139] Understandably, by adaptively configuring the sign function parameters of the sliding mode control term based on the position and speed observation errors, real-time dynamic optimization of the sliding mode gain can be achieved. Compared to fixed parameters, this allows for flexible adjustment of the control strength according to the magnitude of the error, suppressing high-frequency chattering and noise amplification at low speeds while ensuring rapid response under high dynamic conditions, thus balancing observation accuracy and stability. Error closed-loop adjustment can quickly reduce observation deviations, improve the accuracy of preliminary position estimation, and accelerate error convergence. Simultaneously, adaptive parameter adjustment eliminates reliance on manual experience tuning, allowing the observer to maintain stable output under complex conditions such as load fluctuations and sudden speed changes, enhancing robustness across all operating conditions.

[0140] Specifically, the process of configuring the parameters of the sign function of the sliding mode control term in the basic model of the full fractional sliding mode observer, based on the position observation error and the rotational speed observation error, to obtain the fully configured full fractional sliding mode observer model can include:

[0141] S141. Adjust the gain coefficient of the sliding mode control term in the basic model of the full fractional sliding mode observer using the following formula:

[0142]

[0143] in, This represents the gain coefficient of the sliding mode control term. This is the initial value of the gain. For gain adjustment step size, This represents the absolute value of the position observation error. This represents the absolute value of the speed observation error.

[0144] S142. Update the sliding mode control term using the gain coefficient to obtain the fully configured full fractional sliding mode observer model.

[0145] The updated sliding mode control item is: .

[0146] Step S150: Construct the state evolution equation of the fractional-order PLL control law, and determine the position estimate and speed estimate of the permanent magnet synchronous motor based on the preliminary position estimate and the state evolution equation.

[0147] The state evolution equation of the fractional-order PLL control law is as follows:

[0148]

[0149] in, For fractional differential operators, For the order of fractional differential operators, This is the position estimate for the permanent magnet synchronous motor. This is an estimated speed value for the permanent magnet synchronous motor. This is the PLL scaling factor. For PLL integral coefficients, For the state evolution equation Fractional integral operator.

[0150] Based on this, the process of determining the position estimate and speed estimate of the permanent magnet synchronous motor based on the preliminary position estimate and the state evolution equation in step S150 may include:

[0151] Substituting the initial position estimate into the state evolution equation, the position and speed estimates of the permanent magnet synchronous motor are obtained by driving the PLL state evolution with the position observation error.

[0152] Specifically, the preliminary position estimate output by the full fractional sliding mode observer model can be used. ( , , Substituting the back electromotive force (the output of the full fractional sliding mode observer model) into the state evolution equation... The position, and then the position observation error. Drive the PLL state evolution and output the final position estimate. Compared with the estimated speed .

[0153] Next, the convergence of the observation process of the position and speed of the permanent magnet synchronous motor in this application will be verified.

[0154] First, we can construct the Lyapunov function corresponding to the fractional-order system and select the Lyapunov function that is suitable for the fractional-order system:

[0155]

[0156] Then, verify that the derivative of the Lyapunov function satisfies the negative definite condition. Based on the properties of Caputo fractional derivatives, ... Find the Caputo fractional derivative:

[0157]

[0158] Combining fractional derivative analysis of the sliding surface (when )hour, Therefore ;

[0159] Similarly and fractional derivative analysis of positional error (when )hour, Therefore , can be obtained According to Lyapunov's stability theorem for fractional-order systems, when the Caputo fractional derivative of the Lyapunov function is negative, the system state (current observation error, position observation error) will converge to 0, meaning that the full fractional-order position-speed observation process is globally asymptotically convergent.

[0160] The method for estimating the position and speed of a permanent magnet synchronous motor (PMSM) provided in this embodiment obtains the operating electrical data and control configuration parameters of the PMSM in response to a sensorless control request. Based on the operating electrical data and control configuration parameters, observation modeling is performed to obtain a basic model of a full fractional sliding mode observer. According to the output observation data of the basic model of the full fractional sliding mode observer and the state data of the PMSM, the position observation error and speed observation error of the PMSM are determined. Based on the position observation error and speed observation error, the parameters of the sign function of the sliding mode control term in the basic model of the full fractional sliding mode observer are configured to obtain the fully configured full fractional sliding mode observer model. The preliminary position estimate output by the full fractional sliding mode observer model is obtained. Based on the preliminary position estimate and the state evolution equation of the fractional PLL control law, the position and speed estimates are determined. Therefore, by adopting a full fractional sliding mode observer, the flexible characteristics of fractional operators are used to suppress chattering and reduce the impact of noise; the sliding mode control parameters are adaptively adjusted with the observation error to accelerate error convergence; and the position and speed estimation are precisely coupled through fractional PLL, thereby comprehensively improving the observation accuracy, convergence speed and stability under all operating conditions.

[0161] The apparatus for estimating the position and speed of a permanent magnet synchronous motor provided in the embodiments of this application will be described below. The apparatus for estimating the position and speed of a permanent magnet synchronous motor described below can be referred to in correspondence with the method for estimating the position and speed of a permanent magnet synchronous motor described above.

[0162] See Figure 3 , Figure 3 This is a schematic diagram of a device for estimating the position and speed of a permanent magnet synchronous motor, as disclosed in an embodiment of this application.

[0163] like Figure 3 As shown, the device may include:

[0164] The data parameter acquisition module 11 is used to respond to the sensorless control request of the permanent magnet synchronous motor and acquire the operating electrical data and control configuration parameters of the permanent magnet synchronous motor.

[0165] Model building module 12 is used to perform observation modeling based on the operating electrical data and the control configuration parameters to obtain the basic model of the full fractional sliding mode observer;

[0166] The observation error determination module 13 is used to determine the position observation error and speed observation error of the permanent magnet synchronous motor based on the output observation data of the full fractional sliding mode observer basic model and the state data of the permanent magnet synchronous motor.

[0167] The model configuration module 14 is used to configure the parameters of the sign function of the sliding mode control term in the basic model of the full fractional sliding mode observer based on the position observation error and the rotational speed observation error, so as to obtain the fully configured full fractional sliding mode observer model and obtain the preliminary position estimate output by the full fractional sliding mode observer model.

[0168] The estimation output module 15 is used to construct the state evolution equation of the fractional-order PLL control law, and determine the position estimate and speed estimate of the permanent magnet synchronous motor based on the preliminary position estimate and the state evolution equation.

[0169] Optionally, the operating electrical data includes stator three-phase voltage and stator three-phase current;

[0170] The model building module includes:

[0171] The voltage component conversion module is used to convert the three-phase stator voltage into electrical quantities to obtain two-phase voltage components;

[0172] The current component conversion module is used to convert the three-phase stator current into electrical quantities to obtain two-phase current components;

[0173] The equation construction module is used to construct the stator voltage equation and the current observation equation based on the two-phase voltage components and the two-phase current components;

[0174] A fractional-order sliding surface construction module is used to construct the current observation error and, based on the control configuration parameters and the current observation error, construct a fractional-order sliding surface.

[0175] The state evolution equation construction module is used to construct a sliding mode control term through the current observation error, and based on the sliding mode control term and the current observation equation, construct a state evolution equation to obtain the basic model of the full fractional sliding mode observer;

[0176] Optionally, the observation error determination module includes:

[0177] The back electromotive force observation extraction module is used to extract the back electromotive force observations of the basic model of the full fractional sliding mode observer.

[0178] The position and rotational speed first estimate calculation module is used to calculate the first estimate of position using the back electromotive force observation value, and differentiate the first estimate of position to obtain the first estimate of rotational speed;

[0179] An error determination module is used to determine the position observation error between the first estimated position value and the actual position of the permanent magnet synchronous motor, and the speed observation error between the first estimated speed value and the actual speed of the permanent magnet synchronous motor.

[0180] Optionally, the model configuration module includes:

[0181] The gain coefficient adjustment module is used to adjust the gain coefficient of the sliding control term in the basic model of the full fractional sliding mode observer using the following formula:

[0182]

[0183] in, The gain coefficient of the sliding mode control term. This is the initial value of the gain. For gain adjustment step size, The absolute value of the position observation error. This is the absolute value of the observed rotational speed error;

[0184] The sliding mode control term update module is used to update the sliding mode control term using the gain coefficient to obtain a fully configured full fractional sliding mode observer model and to obtain the preliminary position estimate output by the full fractional sliding mode observer model.

[0185] Optionally, the state evolution equation of the fractional-order PLL control law is:

[0186]

[0187] in, For fractional differential operators, For the order of fractional differential operators, This is the estimated position value of the permanent magnet synchronous motor. This is the estimated speed of the permanent magnet synchronous motor. This is the PLL scaling factor. For PLL integral coefficients, For the state evolution equation Fractional integral operator;

[0188] The estimated value output module includes:

[0189] The estimation output submodule is used to substitute the preliminary position estimate into the state evolution equation, and drive the PLL state evolution with the position observation error to obtain the position estimate and speed estimate of the permanent magnet synchronous motor.

[0190] Optionally, the fractional-order sliding surface can be in the following form:

[0191]

[0192] in, This represents the α phase after Clark transformation. This represents the β phase after Clark transformation. For the α phase of the fractional-order sliding surface, For the β phase of the fractional-order sliding surface, For fractional differential operators, For the order of fractional differential operators, , This is the sliding surface adjustment coefficient. , The current observation error for phase α is... The current observation error for phase β.

[0193] Optionally, the device may also include:

[0194] The fractional-order sliding surface discretization module is used to discretize the fractional-order sliding surface, resulting in the following discretized fractional-order sliding surface:

[0195]

[0196] in, For the α phase of the discretized fractional-order sliding surface, For the β phase of the discretized fractional-order sliding surface, The gain coefficient of the sliding mode control term. This is the sampling step size.

[0197] The device for estimating the position and speed of a permanent magnet synchronous motor provided in this application embodiment can be applied to devices for estimating the position and speed of a permanent magnet synchronous motor, such as terminals like mobile phones and computers. Optionally, Figure 4 The hardware block diagram of the device for estimating the position and speed of a permanent magnet synchronous motor is shown. (Refer to...) Figure 4 The hardware structure of the device may include: at least one processor 1, at least one communication interface 2, at least one memory 3, and at least one communication bus 4;

[0198] In this embodiment of the application, the number of processor 1, communication interface 2, memory 3, and communication bus 4 is at least one, and processor 1, communication interface 2, and memory 3 communicate with each other through communication bus 4;

[0199] Processor 1 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention.

[0200] Memory 3 may include high-speed RAM, and may also include non-volatile memory, such as at least one disk storage device;

[0201] The memory stores a program, which the processor can call. The program is used for:

[0202] In response to a sensorless control request for a permanent magnet synchronous motor, the system acquires the operating electrical data and control configuration parameters of the permanent magnet synchronous motor.

[0203] Based on the aforementioned operational electrical data and control configuration parameters, observation modeling is performed to obtain the basic model of the full fractional sliding mode observer;

[0204] Based on the output observation data of the full fractional sliding mode observer basic model and the state data of the permanent magnet synchronous motor, the position observation error and speed observation error of the permanent magnet synchronous motor are determined.

[0205] Based on the position observation error and the rotational speed observation error, the parameters of the sign function of the sliding mode control term in the full fractional sliding mode observer basic model are configured to obtain the fully configured full fractional sliding mode observer model, and the preliminary position estimate output by the full fractional sliding mode observer model is obtained.

[0206] A state evolution equation for a fractional-order PLL control law is constructed, and based on the preliminary position estimate and the state evolution equation, the position estimate and speed estimate of the permanent magnet synchronous motor are determined.

[0207] Optionally, the refined and extended functions of the program can be found in the description above.

[0208] This application embodiment also provides a storage medium that can store a program suitable for execution by a processor, the program being used for:

[0209] In response to a sensorless control request for a permanent magnet synchronous motor, the system acquires the operating electrical data and control configuration parameters of the permanent magnet synchronous motor.

[0210] Based on the aforementioned operational electrical data and control configuration parameters, observation modeling is performed to obtain the basic model of the full fractional sliding mode observer;

[0211] Based on the output observation data of the full fractional sliding mode observer basic model and the state data of the permanent magnet synchronous motor, the position observation error and speed observation error of the permanent magnet synchronous motor are determined.

[0212] Based on the position observation error and the rotational speed observation error, the parameters of the sign function of the sliding mode control term in the full fractional sliding mode observer basic model are configured to obtain the fully configured full fractional sliding mode observer model, and the preliminary position estimate output by the full fractional sliding mode observer model is obtained.

[0213] A state evolution equation for a fractional-order PLL control law is constructed, and based on the preliminary position estimate and the state evolution equation, the position estimate and speed estimate of the permanent magnet synchronous motor are determined.

[0214] Optionally, the refined and extended functions of the program can be found in the description above.

[0215] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0216] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0217] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for estimating the position and speed of a permanent magnet synchronous motor, characterized in that, include: In response to a sensorless control request for a permanent magnet synchronous motor, the system acquires the operating electrical data and control configuration parameters of the permanent magnet synchronous motor. Based on the aforementioned operational electrical data and control configuration parameters, observation modeling is performed to obtain the basic model of the full fractional sliding mode observer; Based on the output observation data of the full fractional sliding mode observer basic model and the state data of the permanent magnet synchronous motor, the position observation error and speed observation error of the permanent magnet synchronous motor are determined. Based on the position observation error and the rotational speed observation error, the parameters of the sign function of the sliding mode control term in the full fractional sliding mode observer basic model are configured to obtain the fully configured full fractional sliding mode observer model, and the preliminary position estimate output by the full fractional sliding mode observer model is obtained. A state evolution equation for a fractional-order PLL control law is constructed, and based on the preliminary position estimate and the state evolution equation, the position estimate and speed estimate of the permanent magnet synchronous motor are determined.

2. The method according to claim 1, characterized in that, The operating electrical data includes stator three-phase voltage and stator three-phase current; Based on the aforementioned operational electrical data and control configuration parameters, observation modeling is performed to obtain the basic model of the full fractional-order sliding mode observer, including: The three-phase stator voltage is converted into two-phase voltage components by electrical quantity conversion. The three-phase stator current is converted into electrical quantities to obtain two-phase current components; Based on the two-phase voltage components and the two-phase current components, the stator voltage equation and the current observation equation are constructed. A current observation error is constructed, and a fractional-order sliding surface is constructed based on the control configuration parameters and the current observation error; A sliding mode control term is constructed using the current observation error, and a state evolution equation is constructed based on the sliding mode control term and the current observation equation to obtain the basic model of the full fractional sliding mode observer.

3. The method according to claim 2, characterized in that, Based on the output observation data of the full fractional-order sliding mode observer basic model and the state data of the permanent magnet synchronous motor, the position observation error and speed observation error of the permanent magnet synchronous motor are determined, including: Extract the back electromotive force observation value of the basic model of the full fractional sliding mode observer; The first estimated value of the position is calculated using the observed back electromotive force, and the first estimated value of the rotational speed is obtained by differentiating the first estimated value of the position. Determine the position observation error between the first estimated position and the actual position of the permanent magnet synchronous motor, and the speed observation error between the first estimated speed and the actual speed of the permanent magnet synchronous motor.

4. The method according to claim 2, characterized in that, Based on the position observation error and the rotational speed observation error, the parameters of the sign function of the sliding mode control term in the full fractional sliding mode observer basic model are configured to obtain the fully configured full fractional sliding mode observer model, including: The gain coefficient of the sliding control term in the basic model of the full fractional sliding observer is adjusted by the following formula: in, The gain coefficient of the sliding mode control term. This is the initial value of the gain. For gain adjustment step size, The absolute value of the position observation error. The absolute value of the speed observation error; The sliding mode control term is updated using the gain coefficient to obtain a fully configured full fractional sliding mode observer model.

5. The method according to claim 4, characterized in that, The state evolution equation of the fractional-order PLL control law is as follows: in, For fractional differential operators, For the order of fractional differential operators, This is the estimated position value of the permanent magnet synchronous motor. This is the estimated speed of the permanent magnet synchronous motor. This is the PLL scaling factor. For PLL integral coefficients, For the state evolution equation Fractional integral operator; Based on the preliminary position estimate and the state evolution equation, the position estimate and speed estimate of the permanent magnet synchronous motor are determined, including: Substituting the preliminary position estimate into the state evolution equation, the position observation error drives the PLL state evolution to obtain the position estimate and speed estimate of the permanent magnet synchronous motor.

6. The method according to any one of claims 2-5, characterized in that, The fractional-order sliding surface has the following form: in, This represents the α phase after Clark transformation. This represents the β phase after Clark transformation. For the α phase of the fractional-order sliding surface, For the β phase of the fractional-order sliding surface, For fractional differential operators, For the order of fractional differential operators, , This is the sliding surface adjustment coefficient. , The current observation error for phase α is... The current observation error for phase β.

7. The method according to claim 6, characterized in that, Also includes: Discretizing the fractional-order sliding surface yields the discretized fractional-order sliding surface as follows: in, For the α phase of the discretized fractional-order sliding surface, For the β phase of the discretized fractional-order sliding surface, The gain coefficient of the sliding mode control term. This is the sampling step size.

8. A device for estimating the position and speed of a permanent magnet synchronous motor, characterized in that, include: The data parameter acquisition module is used to respond to the sensorless control request of the permanent magnet synchronous motor and acquire the operating electrical data and control configuration parameters of the permanent magnet synchronous motor. The model building module is used to perform observation modeling based on the operating electrical data and the control configuration parameters to obtain the basic model of the full fractional sliding mode observer; The observation error determination module is used to determine the position observation error and speed observation error of the permanent magnet synchronous motor based on the output observation data of the full fractional sliding mode observer basic model and the state data of the permanent magnet synchronous motor. The model configuration module is used to configure the parameters of the sign function of the sliding control term in the basic model of the full fractional sliding mode observer based on the position observation error and the rotational speed observation error, so as to obtain the fully configured full fractional sliding mode observer model and obtain the preliminary position estimate output by the full fractional sliding mode observer model. The estimation output module is used to construct the state evolution equation of the fractional-order PLL control law, and based on the preliminary position estimate and the state evolution equation, determine the position estimate and speed estimate of the permanent magnet synchronous motor.

9. A device for estimating the position and speed of a permanent magnet synchronous motor, characterized in that, Including memory and processor; The memory is used to store programs; The processor is configured to execute the program to implement the various steps of the method for estimating the position and speed of a permanent magnet synchronous motor as described in any one of claims 1-7.

10. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements each step of the method for estimating the position and speed of a permanent magnet synchronous motor as described in any one of claims 1-7.

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