Optimal Power Distribution Strategy for Series-Parallel Hybrid Electric Vehicles

Abstract

The series-parallel hybrid electric vehicle, which employs a planetary gear set to combine one internal combustion engine and two electric motors, can take advantages of both series and parallel hybrid system by controlling power flows. In this system, the control of power flows means adjusting not only the amount and direction of mechanical and electrical power but also the operating point of the engine. This study introduces the power distribution strategy which uses control maps to minimize the loss in power flow and operate engine on efficient point. And the control maps can be obtained by optimization process seeking efficient operating point for the given speed, load and battery charge/discharge power. The suggested strategy distributes the power flows efficiently and further, it helps to build energy control strategy since battery power can be controlled easily.I.

Study on Power-Train Configuration of Hybrid Electric Vehicle Equipped with Dual Clutch Transmission

“…The electric energy consumed by motor-driven or created by power generation is equivalent to some fuel energy. The equivalent coefficient(8.834 kW•h/L) [5] between them can refer to standard SAEJ1711. The total fuel consumption can be got according to the standard, as show in Tab.2.…”

Stochastic Optimal Control of Parallel Hybrid Electric Vehicles

“…Extensive literature has dealt with the EMS design [1,2]. In the automotive industry, the rule-based control strategies, from thermostat strategy, power follower control strategy, and engine optimal working point strategy to fuzzy rule based techniques (e.g., conventional fuzzy strategy, adaptive fuzzy logic strategy and fuzzy Q-Learning strategy), were developed on the basis of experimental trials and engineering experiences for their effectiveness in real time control [3][4][5][6][7][8][9][10]. However, the nature of results limited to specific vehicle design and not coping with multiple objects limits the application of these rule-based control strategies in HEVs.…”