A nonlinear optimal control system for hybrid excitation synchronous electric drive

Abstract

The present invention belongs to the technical field of electric vehicles, and discloses a nonlinear optimal control system of a hybrid excitation synchronous electric drive, comprising: a hybrid power unit, the hybrid power unit comprising a gasoline engine, a hybrid double excitation synchronous motor and an AC / DC converter; a dynamic model unit established based on the AC / DC converter; a dynamic model unit 1 established based on the hybrid double excitation synchronous motor; a dynamic model unit 2 established based on the gasoline engine; a linearized model unit established based on the dynamic model unit, the dynamic model unit 1 and the dynamic model unit 2; and an H-infinity nonlinear feedback controller established based on the linearized model unit. The H-infinity controller provides a solution to the nonlinear optimal control problem of a hybrid powertrain under model uncertainty and external disturbances.

Description

Technical Field

[0001] The invention belongs to the technical field of electric vehicles, and in particular relates to a nonlinear optimal control system of a hybrid excitation synchronous electric drive. Background Art

[0002] The powertrain of a hybrid vehicle usually consists of an internal combustion engine (diesel, gasoline engine, or even hydrogen power stack), which provides torque for the driving movement of a synchronous or asynchronous electric machine, where this torque can be used as a generator, or as a drive motor. In generator mode, the electric machine provides power to the vehicle's electrical loads and battery pack, while in drive motor mode, it provides traction for the vehicle. The alternating voltage of the generator is converted to a direct voltage by an AC / DC converter, allowing the vehicle's electrical loads to be powered and the energy storage (battery) to be charged.

[0003] The control of the energy storage (battery) and drive system of a hybrid vehicle is a very difficult problem due to the nonlinear and multivariable structure of its system state space model. In fact, the solution of the control problem of the integrated energy storage (battery) and drive system consisting of a gasoline engine, a hybrid (double) excited synchronous generator and an AC / DC converter is very universal and needs to be handled with a general approach. On the other hand, the solution of the nonlinear control problem of the hybrid powertrain is very important and necessary, because it can ensure and improve the performance and safety challenges of the power drive system. Existing solutions do not optimize energy consumption and do not minimize the losses of the energy storage (battery) and drive system of the hybrid system. Summary of the invention

[0004] The object of the present invention is to provide a nonlinear optimal control system for a hybrid excitation synchronous electric drive to solve the problems in the prior art mentioned in the above background technology.

[0005] To achieve the above-mentioned purpose, the present invention adopts the following technical scheme: a nonlinear optimal control system of a hybrid excitation synchronous electric drive, comprising: a hybrid power unit, the hybrid power unit comprising a gasoline engine, a hybrid double-excitation synchronous motor and an AC / DC converter; a dynamic model unit established based on the AC / DC converter; a dynamic model unit 1 established based on the hybrid double-excitation synchronous motor; a dynamic model unit 2 established based on the gasoline engine; a linearized model unit established based on the dynamic model unit, the dynamic model unit 1 and the dynamic model unit 2; and an H-infinity nonlinear feedback controller established based on the linearized model unit.

[0006] Preferably, the expression of the dynamic model unit is as follows:

[0007]

[0008]

[0009]

[0010] Among them, i d 、i q is the phase current ia, ib, ic after transformation in the dq reference system, equivalently v d 、v q is the phase voltage va, vb, vc after transformation in the dq reference frame; variable V dc represents the DC voltage output of the converter, u1 = _d, u2 = _q represents the control input, the resistor R represents the line loss and any conduction loss, and the resistor R c Represents the inverter switching loss.

[0011] Preferably, the expression of the kinetic model unit 1 is as follows:

[0012]

[0013]

[0014]

[0015]

[0016]

[0017] Among them, v sd is the d-axis component of the stator voltage, v sq is the q-axis component of the stator voltage, v f is the excitation (field) voltage at the stator auxiliary winding, i sd is the d-axis component of the stator current, i sq is the q-axis component of the stator current; if it is the current in the stator auxiliary excitation circuit, R is the resistance of each phase of the stator, R f is the resistance of the auxiliary excitation winding, L d is the d-axis component of the stator inductance, L q is the q-axis component of the stator inductance, L f is the inductance of the auxiliary field winding.

[0018] Preferably, the expression of the kinetic model unit 2 is as follows:

[0019]

[0020] Preferably, the expression of the linearized model unit is as follows:

[0021]

[0022] Among them, A is the state coefficient matrix, B is the control coefficient matrix, x is the n-dimensional state vector, and u is the r-dimensional control vector.

[0023] Preferably, the H-infinity nonlinear feedback controller performs a first approximate linearization through a first-order Taylor series expansion and related Jacobian matrix calculation, and the linearization point is defined by the present value of the system state vector and the last sampled value of the control input vector at each sampling moment.

[0024] Preferably, it also includes an excitation control system, which includes an excitation power unit, an excitation controller and a synchronous generator;

[0025] Among them, the excitation power unit is mainly responsible for providing excitation current to the synchronous generator rotor. In essence, it is a controllable DC power supply dedicated to the generator. The excitation controller detects the voltage, current, power, speed and other state quantities of the synchronous generator, sends a control signal to the excitation power unit according to the specified control law, controls the output of the excitation power unit, and realizes the control of the excitation system.

[0026] Preferably, the relationship between the rotor angle and acceleration of the synchronous generator and the torque acting on the generator set is:

[0027] Jα=M m -M e -M D

[0028] Where, α is the generator rotor angular acceleration, M m is the mechanical torque of the prime mover acting on the main shaft of the generator set, M e is the electromagnetic torque of the generator, which is braking, M D is the damping torque proportional to the torque change, and J is the moment of inertia of the generator rotor.

[0029] Preferably, the expression of the active power of the synchronous generator is:

[0030] P e =v a i a +v b i b +v c i c

[0031] After coordinate transformation, the active power of the generator can also be expressed as:

[0032] P e =v d i d +vq i q

[0033] The corresponding voltage and current are the direct-axis and quadrature-axis voltage and current values ​​of the generator, which can be expressed by the following formulas:

[0034] v d =V t sinδ

[0035] v q =V t cosδ

[0036]

[0037]

[0038] So the power equation of the generator can be expressed as:

[0039]

[0040] Preferably, the field winding voltage expression of the synchronous generator is:

[0041]

[0042] Among them, V f is the excitation winding voltage, I f is the excitation current, is the total flux linkage of the excitation winding, r f is the field winding resistance.

[0043] Technical effects and advantages of the present invention: Compared with the prior art, the nonlinear optimal control system of a hybrid excitation synchronous electric drive proposed in the present invention has the following advantages:

[0044] 1. In the first stage of the present invention, the state space model of the system has undergone approximate linearization by using a first-order Taylor series expansion and by calculating the relevant Jacobian matrix. Then, the linearization point is updated in each iteration of the control algorithm and is defined by the current value of the system state vector and the last sampled value of the control input vector at each sampling instance. For the approximate linearized model of the HEV powertrain, a (H-infinity) controller with optimal system stability performance is established. The H-infinity controller provides a solution to the nonlinear optimal control problem of the hybrid powertrain under model uncertainty and external disturbances.

[0045] 2. The stability of the control algorithm of the present invention has been proved through analysis and further confirmed in simulation experiments. Under the proposed nonlinear optimal control scheme, it is possible to ensure that the state variables of the hybrid powertrain track the reference set values ​​quickly and accurately while maintaining moderate changes in the control input. By constraining the changes in the control input, the control method of the present invention minimizes energy dispersion through the HEV's power generation and drive systems, and improves the autonomy and operating capability of the hybrid power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 A diagram of a hybrid powertrain in an embodiment of the present invention;

[0047] Figure 2 Schematic diagram of the H-infinity control scheme of the hybrid powertrain in an embodiment of the present invention;

[0048] Figure 3 1 is a block diagram of an automatic control system for excitation of a generator in an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. The specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0050] In the embodiment of the present invention, there is provided Figure 1-3 A nonlinear optimal control system for a hybrid excitation synchronous electric drive is shown in Figure 1. The proposed H-infinity controller in this system solves the optimal control problem of the hybrid system energy storage (battery) and drive system under model uncertainty and external disturbances. In fact, the H-infinity control method implements a minimum-maximum differential arbitration, which occurs between (i) control inputs, which try to minimize a quadratic function of the state vector tracking error, and (ii) model uncertainties and disturbance terms, which try to maximize this cost function. In order to select the stable feedback gain of the proposed H-infinity controller, the algebraic Riccati equation is repeatedly solved at each time step of the control algorithm. The global stability of the control scheme is proved by Lyapunov analysis.

[0051] First, it is demonstrated that the control loops of the hybrid powertrain’s energy storage (battery) and drive system achieve H-infinity tracking performance, which represents robustness to model uncertainties and exogenous disturbances. Furthermore, the control approach is proven to be globally asymptotically stable under moderate conditions. Finally, in order to implement state estimation-based control without measuring the entire state vector of the HEV powertrain, an H-infinity Kalman filter is used as a robust state estimator. It is shown that the H-infinity control scheme achieves fast and accurate tracking of the reference set point under moderate variations of the control input. Furthermore, by minimizing the variations in the control signals, it reduces the dispersion of energy in the hybrid drive system, thereby improving the vehicle’s autonomy and operational capabilities.

[0052] Specifically, it includes: a hybrid power unit, which includes a gasoline engine, a hybrid double-excitation synchronous motor and an AC / DC converter; a dynamic model unit established based on the AC / DC converter; a dynamic model unit 1 established based on the hybrid double-excitation synchronous motor; a dynamic model unit 2 established based on the gasoline engine; a linearized model unit established based on the dynamic model unit, the dynamic model unit 1 and the dynamic model unit 2; and an H-infinity nonlinear feedback controller established based on the linearized model unit.

[0053] The expression of the dynamic model unit is as follows:

[0054]

[0055]

[0056]

[0057] Among them, i d 、i q is the phase current ia, ib, ic after transformation in the dq reference system, equivalently v d 、v q is the phase voltage va, vb, vc after transformation in the dq reference frame; variable V dc represents the DC voltage output of the converter, u1 = _d, u2 = _q represents the control input, the resistor R represents the line loss and any conduction loss, and the resistor R c Represents the inverter switching loss.

[0058] The expression of the kinetic model unit 1 is as follows:

[0059]

[0060]

[0061]

[0062]

[0063]

[0064] The doubly excited synchronous motor receives dual excitation via (i) an AC / DC and DC / AC converter connected to the stator winding, and (ii) a DC / DC converter connected to the auxiliary winding of the stator. To describe the electrodynamics of the motor, a synchronously rotating dq reference frame is adopted. The parameters and state variables of the HESG model are defined as follows: sd is the d-axis component of the stator voltage, v sq is the q-axis component of the stator voltage, v f is the excitation (field) voltage at the stator auxiliary winding, i sd is the d-axis component of the stator current, i sq is the q-axis component of the stator current; if it is the current in the stator auxiliary excitation circuit, R is the resistance of each phase of the stator, R f is the resistance of the auxiliary excitation winding, L d is the d-axis component of the stator inductance, L q is the q-axis component of the stator inductance, L f is the inductance of the auxiliary field winding.

[0065] The expression of the kinetic model unit 2 is as follows:

[0066] The expression of the linearized model unit is as follows: Among them, A is the state coefficient matrix, B is the control coefficient matrix, x is the n-dimensional state vector, and u is the r-dimensional control vector.

[0067] The H-infinity nonlinear feedback controller is first approximated linearized by a first order Taylor series expansion and the associated Jacobian matrix calculation, the linearization point being defined at each sampling instant by the present value of the system state vector and the last sampled value of the control input vector. The solution of the H-infinity feedback controller for the hybrid energy storage (battery) / drive system and the calculation of the worst case disturbance that the controller can withstand are derived from the superposition of the Bellman optimality principle when considering the hybrid powertrain to be subject to two separate inputs (i) the control input u and (ii) the cumulative disturbance input d(t). The optimal control problem is solved for u, i.e. the minimum change (optimal) control input to achieve the elimination of the state vector tracking error. Equivalently, the optimal control problem is solved for d(t), i.e. the worst case disturbance that the control loop can withstand.

[0068] The control of a HEV powertrain consisting of an internal combustion engine, a hybrid (double) excited synchronous motor and an AC / DC converter is a non-trivial problem due to the nonlinear and multivariable structure of the associated state-space model. The present invention successfully applies the above nonlinear optimal (H-infinity) control method to the above energy and drive system of a hybrid electric vehicle. In a first stage, the state-space model of the system has undergone an approximate linearization by using a first-order Taylor series expansion and by calculating the associated Jacobian matrix. Then, the linearization point is updated in each iteration of the control algorithm and is defined at each sampling instance by the current value of the system state vector and the last sampled value of the control input vector. For the approximate linearized model of the HEV powertrain, a (H-infinity) controller with optimal system stability performance is successfully established.

[0069] The proposed H-infinity controller provides a solution to the nonlinear optimal control problem of a hybrid powertrain under model uncertainty and external disturbances. To calculate the feedback gains of this controller, the algebraic Riccati equations have to be solved repeatedly at each time step of the control algorithm. The global stability properties of the proposed control scheme have been confirmed using a Lyapunov analysis.

[0070] The stability of the control algorithm of the present invention is proved by analysis and further confirmed in simulation experiments. Under the proposed nonlinear optimal control scheme, the state variables of the hybrid powertrain can be guaranteed to track the reference set values ​​quickly and accurately while maintaining moderate changes in the control input. By constraining the changes in the control input, the control method of the present invention minimizes the energy dispersion through the power generation and drive systems of the HEV and improves the autonomy and operating capability of the hybrid powertrain.

[0071] It is worth noting that common methods used to perform nonlinear optimal control in industry, such as nonlinear model predictive control, do not always have proven global stability, and the convergence of their iterative search for the optimum often depends on the choice of parameter values ​​and initial conditions (multiple shooting methods). Compared with the LPV (Linear Parameter Variation) method for applying optimal control, the nonlinear optimal control method proposed in this invention is universal and is not limited to a specific form and structure of the state space model.

[0072] Furthermore, the proposed nonlinear optimal control scheme has advantages over other nonlinear control methods that can be considered for electric vehicle powertrains. For example, in the case of sliding model control, the selection of the sliding surface is an empirical process unless the controlled system is converted to input-output linearized form. Moreover, in the case of back-off control, if the controlled system is not found to enter the strict feedback (triangular) form, the application of the back-off control method is not supported.

[0073] It also includes an excitation control system, which includes an excitation power unit, an excitation controller and a synchronous generator; wherein the excitation power unit is mainly responsible for providing excitation current to the synchronous generator rotor, and is essentially a controllable DC power supply dedicated to the generator, and the excitation controller detects the voltage, current, power, speed and other state quantities of the synchronous generator, sends a control signal to the excitation power unit according to a specified control law, controls the output of the excitation power unit, and realizes control of the excitation system.

[0074] The relationship between the rotor angle, acceleration and torque acting on the generator set of the synchronous generator is:

[0075] Jα=M m -M e -M D

[0076] Where, α is the generator rotor angular acceleration, M m is the mechanical torque of the prime mover acting on the main shaft of the generator set, M e is the electromagnetic torque of the generator, which is braking, M D is the damping torque proportional to the torque change, and J is the moment of inertia of the generator rotor.

[0077] The expression of the active power of the synchronous generator is:

[0078] P e =v a i a +v b i b +v c i c

[0079] After coordinate transformation, the active power of the generator can also be expressed as:

[0080] P e =v d i d +v q i q

[0081] The corresponding voltage and current are the direct-axis and quadrature-axis voltage and current values ​​of the generator, which can be expressed by the following formulas:

[0082] v d =V t sinδ

[0083] v q =V t cosδ

[0084]

[0085]

[0086] So the power equation of the generator can be expressed as:

[0087]

[0088] If it is a hidden pole machine, because x q =x d , so its active power expression is:

[0089]

[0090] Generator reactive power is defined as:

[0091]

[0092] The reactive power expression sent by the generator to the grid is:

[0093]

[0094] The excitation winding voltage expression of the synchronous generator is:

[0095]

[0096] Among them, V f is the excitation winding voltage, I f is the excitation current, is the total flux linkage of the excitation winding, r f is the field winding resistance.

[0097] The linear optimal excitation control method is used to design a multivariable excitation control method with the goal of improving the dynamic stability of the power system. The gains of the generator voltage regulation channel and other additional excitation control channels are determined at the same time. The dominant position of the voltage regulation channel is not determined, and it is only considered by the weight coefficient method. Although the result can meet the requirements of dynamic stability, it is still uncertain whether it can meet the requirements of voltage regulation. In addition, in the design of linear optimal excitation control, a certain performance indicator is used as the minimum requirement to obtain the control parameters, and the parameters are not considered or cannot be changed when the system operation mode changes, so it has poor robustness.

[0098] Theoretically, the nonlinear excitation regulator has a wider system stability control domain than PSS+PID and linear optimal excitation controller. When artificial intelligence is applied to excitation control, the precise mathematical model of the controlled object is not required. The control effect is determined by the control rules and their adaptive ability to the system operation.

[0099] The nonlinear H theory is applied to the excitation control design, and the integral of the terminal voltage deviation is added as the state variable. A nonlinear robust model of a single-machine-infinite power system is established. The nonlinear H control law is obtained using MATLAB software. Simulation shows that nonlinear H control can quickly quell system oscillations, which not only effectively improves the transient stability of the system and the dynamic performance of the system, but also meets the requirements of voltage accuracy after fault removal. It also has robustness against uncertain modeling error parameters and unknown interference, which indicates an optimistic application prospect.

[0100] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A nonlinear optimal control system for a hybrid excitation synchronous electric drive, characterized in that: include: A hybrid power unit, the hybrid power unit comprising a gasoline engine, a hybrid double-excitation synchronous motor and an AC / DC converter; A dynamic model unit established based on the AC / DC converter; A dynamic model unit 1 established based on the hybrid double-excitation synchronous motor; A second dynamic model unit established based on the gasoline engine; A linearized model unit established based on the dynamic model unit, the kinetic model unit 1 and the kinetic model unit 2; An H-infinity nonlinear feedback controller established based on the linearized model unit; The expression of the dynamic model unit is as follows: Among them, i d 、i q is the phase current ia, ib, ic after transformation in the dq reference system, equivalently v d 、v q is the phase voltage va, vb, vc after transformation in the dq reference frame; variable V dc represents the DC voltage output of the converter, u1 = _d, u2 = _q represents the control input, the resistor R represents the line loss and any conduction loss, and the resistor R c represents the inverter switching loss; The expression of the kinetic model unit 1 is as follows: Among them, v sd is the d-axis component of the stator voltage, v sq is the q-axis component of the stator voltage, v f is the excitation voltage at the stator auxiliary winding, i sd is the d-axis component of the stator current, i sq is the q-axis component of the stator current; if it is the current in the stator auxiliary excitation circuit, R is the resistance of each phase of the stator, R f is the resistance of the auxiliary excitation winding, L d is the d-axis component of the stator inductance, L q is the q-axis component of the stator inductance, L f is the inductance of the auxiliary field winding; The H-infinity nonlinear feedback controller is first approximated linearized by first-order Taylor series expansion and related Jacobian matrix calculation, and the linearization point is defined by the present value of the system state vector and the last sampled value of the control input vector at each sampling time.

2. A nonlinear optimal control system for a hybrid excitation synchronous electric drive according to claim 1, characterized in that: The expression of the kinetic model unit 2 is as follows:

3. The nonlinear optimal control system of a hybrid excitation synchronous electric drive according to claim 2, characterized in that: The expression of the linearized model unit is as follows: Among them, A is the state coefficient matrix, B is the control coefficient matrix, x is the n-dimensional state vector, and u is the r-dimensional control vector.

4. The nonlinear optimal control system of a hybrid excitation synchronous electric drive according to claim 1, characterized in that: Also included is an excitation control system, which includes an excitation power unit, an excitation controller and a synchronous generator; Among them, the excitation power unit is mainly responsible for providing excitation current to the synchronous generator rotor. In essence, it is a controllable DC power supply dedicated to the generator. The excitation controller detects the voltage, current, power and speed of the synchronous generator, sends a control signal to the excitation power unit according to the specified control law, controls the output of the excitation power unit, and realizes the control of the excitation system.

5. The nonlinear optimal control system of a hybrid excitation synchronous electric drive according to claim 4, characterized in that: The relationship between the rotor angle, acceleration and torque acting on the generator set of the synchronous generator is: Jα=M m -M e -M D Where, α is the generator rotor angular acceleration, M m is the mechanical torque of the prime mover acting on the main shaft of the generator set, M e is the electromagnetic torque of the generator, which is braking, M D is the damping torque proportional to the torque change, and J is the moment of inertia of the generator rotor.

6. The nonlinear optimal control system of a hybrid excitation synchronous electric drive according to claim 5, characterized in that: The expression of the active power of the synchronous generator is: P e =v a i a +v b i b +v c i c After coordinate transformation, the active power of the generator is also expressed as: P e =v d i d +v q i q The corresponding voltage and current are the direct-axis and quadrature-axis voltage and current values ​​of the generator, which can be expressed by the following formulas: v d =V t sinδ in q =V t cosδ So the power equation of the generator can be expressed as:

7. The nonlinear optimal control system of a hybrid excitation synchronous electric drive according to claim 6, characterized in that: The excitation winding voltage expression of the synchronous generator is: Among them, V f is the excitation winding voltage, I f is the excitation current, is the total flux linkage of the excitation winding, r f is the field winding resistance.

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