Hybrid Electric Vehicle Control System Design And Simulation

Energy crisis and environmental deterioration are two important problems of global development. The design of low energy consumption and low emissions vehicle can abate the pressure of energy absence and improve the quality of environment. Hybrid electric vehicle (HEV), which has many advantages, such as low energy consumption, low emissions, long drive distance, mature technology etc, is presently a kind of vehicle that most feasible and capable of mass production. Split hybrid electric vehicle (PSHEV) is a new type HEV, which has better performance than Parallel HEV (PHEV). At present, the studies of PSHEV in the global are seldom, and most of which are based on continuous variable transmission. Supported by 863 program of hybrid electric saloon car and using the relevant research achievements of the global for reference, this dissertation uses automated mechanical transmission based PSHEV control system as research object, and uses intelligent technologies, such as fuzzy logic control, neural network, artificial immune network etc, object-oriented iteration increment design method, and model-based simulation technology etc. in the process of PSHEV control system design. A series of new feasible design methods of HEV control system design are proposed. First, a new hybrid modeling method is proposed for building the PSHEV control models, which combines backward modeling method and forward modeling method, -using backward method to confirm the scheme and main parameters of PSHEV, and using forward method to set up detail control system models, thereby maintains the tradeoff between computation speed and models veracity. Second, the energy management strategies (EMS) of PSHEV are studied, and VSC controller is designed. According to PSHEV's unique operating modes, a new EMS is proposed, which adds some operating modes, such as serial operation. HEV is a kind of high non-linear system, the complexity of which needs intelligent technology. Fuzzy neural network energy management controller is designed, which using neural network's self-learning ability to create the fuzzy rules and membership function, and optimize the parameters of membership function. In order to prevent neural network learning get into local extreme points, artificial immune network is used to optimize neural network's weight, and preferable optimization results are gained. Third, the design method of VSC software is researched, and a new generic framework based control system design method is proposed. In order to reduce design difficulty and improve design speed, object-oriented iteration increment design method is used in the process of designing complex real time systems same as HEV. According to genetic framework based design method, whole control system models can be built and simulated in a unified platform, and can create code from models. This method has good perspective. Last, simulation analysis and experimentations are used to validate these methods and models. The results show that compared with normal vehicle, the PSHEV can saving more than 30 percent fuel consumption on NEDC cycle, and emissions reaches Euro III standard. The study of this dissertation has importance for the research of Chinese own low energy consumption and low emissions vehicle, the improvement of vehicle control system design ability and the establishing of automobile electronics development platform that owns proprietary intellectual property rights.