Parameter Matching And Optimal Control Of Plug - In Hybrid Electric Vehicle

Energy shortage, environmental pollution and climate warming have become the difficulties and challenges that the automobile industry is facing. Developing the new low fuel consumption and the low emission vehicles has turned into the primary task of the automobile industry. The Plug-in Hybrid Electric Vehicle (PHEV), which combines the advantages of the internal combustion engine vehicles and the electric vehicles, is one of the effective ways to solve the energy shortage problems and improve the environment condition. And it is also an important development direction for the vehicles in the future. As a new type of the transportation with the multi-energy sources, the design of the dynamic parameters matching and control strategy is the core technology of PHEV and also an important means of improving the dynamic performance as well as the economic performance. Therefore, this paper takes the PHEV as the research object. The dynamic system parameter matching and the energy management control strategy are studied based on the analysis of the vehicle power system structure of the PHEV.First, the power system structure of the PHEV is analyzed in detail, which is the series structure, the parallel structure and the series-parallel structure. And the main work mode, merits and drawbacks of the three structures are summarized. On this basis, the key parts and the key technology are introduced.Second, taking the total cost of the three key parts which are the engine, motor and battery as the objective function, the vehicle quality and the dynamic performance as the constraints to build mathematical model, then use genetic algorithm to optimize the system. Make use of Autonomie to construct PHEV simulation model and carry out a simulation experiment. The results showed that the parameters of engine, motor and battery are basically the same with the optimal results of genetic algorithm. Through this, the applicability of the genetic algorithm for the matching power parameters is verified.At last, a kind of optimal control strategy is proposed which divides the engine into 5 regions and makes the engine work in the high efficiency region with respect to the vehicle demanded power on the basis of the analyzing of the vehicle dynamic model, power balance model, and battery model. The simulation results reveal that the total fuel consumption cost can be significantly reduced by the proposed optimal control strategy, compared with the CD-CS strategy.