Motor torque optimization finite set predictive control parallel computing method

Abstract

The invention relates to a motor torque optimization finite set predictive control parallel computing method, which comprises the following steps of S1, giving a description form of an optimization problem according to a motor torque optimization control target, and obtaining a target function; S2, performing Euler discretization according to a continuous time model of a motor driving system, and constructing a prediction model of the system; and S3, performing parallel computing solution optimization on the prediction model and the target function by adopting a trigger type parallel computing method to realize optimized prediction control on the motor torque. Compared with the prior art, algorithm acceleration is carried out through an assembly line and a parallel computing method, and real-time control over motor torque optimization is achieved.

Description

technical field [0001] The invention relates to the field of motor control, in particular to a parallel computing method for motor torque optimization finite set predictive control. Background technique [0002] The motor drive system is one of the three core technologies of electric vehicles. As the underlying execution unit, it directly affects the yaw stability of the vehicle and the execution of energy management strategies. The effective control of the inverter as the core component of the motor is the motor drive control. key. Considering the discrete switching state of the inverter, the actual system constraints such as the maximum stator current, and multiple control requirements such as motor torque tracking and energy saving, the optimal control of motor torque is a discontinuous multi-objective constrained optimization problem. The finite control set predictive control can display and consider the system constraints, directly optimize the discrete switching varia...

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Problems solved by technology

The finite control set predictive control can display and consider the system constraints, directly optimize the discrete switching variables of the inverter, and realize the multi-objective optimization of the motor torque control, and the switching devices of the inverter generally use high-frequency (tens to hundreds of kHz) IGBT or MOSFET, the switching frequency has high real-time requirements, but the finite set predictive control online ergodic solution has a large computational burden. Therefore, how to improve the computational performance of finite set predictive control is the main bottleneck restricting its application in motor control.

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