Electromechanical coupling driving control for single-shaft parallel hybrid powertrain

The single-shaft parallel hybrid powertrain with the automatic mechanical transmission(AMT)is an efficient hybrid driving system in the hybrid electric bus(HEB),while the electromechanical coupling driving control becomes a complicated question to find a transient optimal control method to distribute the power between the engine and the electric machine(EM).This paper proposes an innovative control method to deal with the complicated transient coupling driving process of the electromechanical coupling driving system,considering the accelerating condition and the cruising condition mostly in the city driving cycle of HEB.The EM might be operated at driving mode or generating mode to assist the diesel engine to work in its high-efficiency area.Therefore,the adaptive torque tracking controller has been brought forward to ensure that the EM implements the demand torque as well as compensate the torque fluctuation of diesel engine.The d?q axis mathematical model and back stepping method are employed to deduce the adaptive controller and its adaptive laws.Simulation results demonstrate that the proposed control scheme can make the output torque of two power sources respond rapidly to the demand torque from the powertrain in the given driving condition.The proposed method could be adopted in the real control of HEB to improve the efficiency of the hybrid driving system.

Multi-objective parameter optimization for a single-shaft series-parallel plug-in hybrid electric bus using genetic algorithm

Recently, the single-shaft series-parallel powertrain of Plug-in Hybrid Electric Bus （PHEB） has become one of the most popu- lar powertrains due to its alterable operating modes, excellent fuel economy and strong adaptability for driving cycles. Never- theless, for configuring the PHEB with single-shaft series-parallel powertrain in the development stage, it still faces greater challenge than other configurations when choosing and matching the main component parameters. Motivated by this issue, a comprehensive multi-objectives optimization strategy based on Genetic Algorithm （GA） is developed for the PHEB with the typical powertrain. First, considering repeatability and regularity of bus route, the methods of off-line data processing and mathematical statistics are adopted, to obtain a representative driving cycle, which could well reflect the general characteristic of the real-world bus route. Then, the economical optimization objective is defined, which is consist of manufacturing costs of the key components and energy consumption, and combined with the dynamical optimization objective, a multi-objective op- timization function is put forward. Meanwhile, GA algorithm is used to optimize the parameters, for the optimal components combination of the novel series-parallel powertrain. Finally, a comparison with the prototype is carried out to verify the per- formance of the optimized powertrain along driving cycles. Simulation results indicate that the parameters of powertrain com- ponents obtained by the proposed comprehensive multi-objectives optimization strategy might get better fuel economy, meanwhile ensure the dynamic performance of PHEB. In contrast to the original, the costs declined by 18%. Hence, the strat- egy would provide a theoretical guidance on parameter selection for PHEB manufacturers.