Study On Parameter Matching Algorithms Of Powertrain For Hybrid Electric Vehicle

With the deteriorating of global environment and the shortage of world’s energy, energy issue has become a major factor restricting the development of automotive industry. Most car manufacturers and scientists are conducting research and making development of new energy vehicles, to break through innovation in energy conservation, reducing fuel consumption and the exhaust. Hydrogen-powered vehicles and pure electric vehicles couldn’t get into mass production because of immature technology. Hybrid electric vehicles (HEV), as the transition of fuel vehicles to electric vehicles, have gradually occupied an important position in the automotive sector.HEV comes from the traditional cars which are equipped with accessories like motors and batteries. It relies on certain control strategies and optimization methods to make coordination between various units, which can save the fuel and reduce the exhaust in the same time. The key components of HEV powertrain include the engine, motor, energy storage device and transmission system. HEV parameter matching is a process of reasonable selection and matching about the specifications and parameters of powertrain components, so as to improve the vehicle fuel economy and emission performance, which in turn could achieve energy saving and environmental protection goals.This paper studied the structure of vehicle powertrain, analyzed the main parameters and realized the analysis of the key components. For parallel hybrid electric vehicles (PHEV), a new idea was proposed to use the minimum principle on parameters matching and optimization program. The driving cycle analysis method was used to determine the total demand power and other important parameters of vehicle powertrain. Mathematical model was established according to the minimum principle. The control variable of system was the hybridization and the state variable was the battery charge state. The objective of the minimum principle was to minimize the total fuel consumption during the entire driving cycles, which was an integral objective related to the power of both the engine and motor. After the optimization of the minimum principle, the least fuel consumption and the least emissions were obtainedThe HEV model was simulated using Matlab and Advisor, and the combinations of various urban driving cycles was chosen as the simulation condition. The results showed that after using the minimum principle, the fuel consumption and the pollutant emissions was reduced significantly. As a result, the fuel consumption of 100km was reduced by 16.17%, the emissions of HC, CO, NOx were reduced respectively by 3.3%,6.3% and 6.9%.