Hybrid electric vehicle self-adaptive PID dynamic control method for improving grey prediction

Abstract

The invention discloses a hybrid electric vehicle self-adaptive PID dynamic control method for improved grey prediction, and the method comprises the following steps: (1) building an improved grey prediction model GM (1, 1); (2) establishing a self-adaptive PID control model; (3) establishing an HEV power driving model; (4) taking a vehicle speed requirement of a typical working condition (NEDC new European driving working condition) as an input; and based on Matlab / Simulink, respectively establishing an adaptive PID closed-loop control HEV driving simulation model based on improved grey prediction and an HEV driving simulation model based on conventional PID closed-loop control, and respectively carrying out comparative simulation analysis on the two models. According to the method, the HEV actual vehicle speed is effectively predicted by establishing the improved grey prediction model, meanwhile, the self-adaptive PID controller with parameters capable of being automatically corrected is established, real-time optimization control is conducted on the HEV power system, the vehicle speed is made to rise rapidly and stably, and the aim of saving energy is truly achieved.

Description

technical field [0001] The invention relates to the technical field of hybrid electric vehicle control, in particular to an adaptive PID dynamic control method for hybrid electric vehicles with improved gray prediction. Background technique [0002] Energy saving and environmental protection are the themes of the current development of the automobile industry, so research on new energy vehicles with high efficiency and energy saving has become a hot spot. The dynamic response of the vehicle speed is seriously affected by the inertia and hysteresis of the system during the driving process of the traditional hybrid electric vehicle (HEV), which cannot meet the requirements of the vehicle speed response to the driving conditions, and due to the nonlinearity of the HEV vehicle system and the time-varying nature of the vehicle speed, It is difficult to achieve control through accurate modeling. In addition, the traditional parallel HEV power system control strategy does not cons...

AI Technical Summary

Problems solved by technology

Although the optimization objectives and optimization methods of various control strategies are focused, they seldom consider the reaction of the dynamic characteristics of HEV to its control strategy. State of the strategy optimization objective

[0004] By adopting conventional vehicle speed PID closed-loop control, the dynamic characteristics of HEV are improved, but excessive pursuit of dynamic characteristics of HEV will result in insufficient driving capability and dynamic response capability of HEV power system, which will make the energy consumption optimization goal of HEV control strategy worse

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