Research On Plug-in 4-mode Hybrid Buses Energy Optimization And Control Method

At present, environmental and energy issues have been a worldwide problem, and is increasingly worse. The fuel consumption of conventional vehicles is growing, and vehicle emission is regarded as an important factor in environmental pollution. Hybrid electric vehicles have advantages over both traditional vehicles and electric vehicles. In this paper, a hybrid vehicle system is introduced, researches are carried on energy management optimization and control strategy, specific tasks of this paper are as follows:Firstly, the system structure and working modes are introduced, and then build system model based on matlab-simulink, including several key power components. There are four alternative operating modes, thus the working status can be more flexible, making sure the system a better fuel economy.Secondly, introducing a parameter λ, which means how much energy the battery offers, then, the equivalent fuel consumption becomes the optimization goal. Based on a known driving cycle,work on off-line global energy optimization is carried out. In this paper, the minimum principle and dynamic programming algorithm are separately used for energy optimization, with SOC balance being the precondition, the fuel consumption is 21.93L/km, 40.02% less than that of a conventional bus.Then, after the offline global optimization, results, including gear distribution, power split, and other useful information, can be extracted and put into use in guiding the hybrid system control strategy and energy management. Then based on the same platform as offline optimization, matlab, real-time simulation program is written, to verify the feasibility and applicability of the energy management strategy. For two driving cycle, with SOC balance being the precondition, fuel consumption was reduced by 41.52% and 40.59% respectively.Finally, genetic algorithm is introduced to optimize those parameters involved in PID controllers, and the control effect satisfies a definite precision and is practicable. Then, according to the energy management strategy presented in this paper, hardware-in-loop simulation is carried out based on DSpace, when SOC reaches a balance, the fuel consumption was reduced by 27.7% and 29.03%, respectively for two driving cycle.