Research On Matching And Control Strategy Of Hybrid Power Train

In the case of dense mobility of urban population, public bus has become indispensable means of transport. But during the operation, public bus consumes a lot of fuel and exhausts a lot of exhaust gas, which makes the quality of urban air more deteriorating and oil resources scarce gradually. Hybrid bus which is integrated with the technologies of internal combustion engine and the advantage of new energy electric buses has become the main development target in bus industry. It is better than traditional buses in fuel economy and overcomes the shortcomings of electric bus, which is limited to the short driving range. Therefore, the study of powertrain match and control strategy has an important significance to the society.The object of this study is a parallel hybrid bus, which is equipped with two independent powertrain systems. Its power system match is to define the parameters of the powertrain components, such as engine power, electrical power, gear ratios, battery capacity and so on, which all of those work is based on powertrain layout and selection of vehicle power systems that have been identified. Use ADVISOR simulation software for rapid prototyping of vehicle power system to match parameters and finally get an optimal powertrain scheme, which is laying the foundation for vehicle modeling and control strategy.Control strategy of Hybrid bus is another key factor affecting vehicle performance and fuel consumption. Based on forward simulation, establish vehicle logic threshold control strategy. Driving intention has been optimized through fuzzy logic control and driving mode switch has been improved by genetic algorithm. All of those improve the vehicle fuel consumption and power performance.HIL test system has been established based on dSPACE in this paper. Download vehicle model to AutoBox toolbox by RTW function and compile vehicle control strategy to HCU. Finally, finish HIL simulation through the CAN bus connection. The test system can verify the rationality of vehicle model and control strategy and realize the functional verification before the vehicle test.