Abstract
The research took a dual-axis-parallel plug-in hybrid electric vehicle (PHEV) as its research object: the engine and electric motor were connected with an automated mechanical transmission (AMT) through two different axles. As the torques of the engine and the electric motor converge through a variety of gear combinations selected within the AMT, the gearshift schedule has a high degree of coupling with the energy management strategy and therefore they jointly determine various aspects of the vehicle performance. Under the coupling constraints of torque and speed of the engine and electric motor, an instantaneous optimal energy management strategy was proposed by considering the influences of torque distribution and gear-matching on the performance of the whole vehicle. By adjusting the torques of the engine and the electric motor, as well as the gear of the AMT independently, the strategy allowed both the engine and the electric motor to operate at a higher efficiency. In this way, the engine, the electric motor, and the AMT can be comprehensively controlled and optimised. The feasibility and effectiveness of the proposed integrated optimisation strategy was proved by simulation on the AVL Cruise and MATLAB™/Simulink platform.
Highlights
Owing to its being equipped with a high battery capacity and a high-power drive motor, the plug in hybrid electric vehicle (PHEV) can travel far with the only support from electrical power, but it can reach an optimal fuel consumption pattern by adjusting the parameter range of the engine through its electric motor
A PHEV is an ideal product in the transition period from traditional vehicles to purely electric vehicles [1]
The optimisation-based energy management strategy [4] is divided into global optimisation [5] represented by the dynamic programming algorithm (DP) and instantaneous optimisation [6,7] represented by the equivalent consumption minimisation strategy (ECMS)
Summary
Owing to its being equipped with a high battery capacity and a high-power drive motor, the plug in hybrid electric vehicle (PHEV) can travel far with the only support from electrical power, but it can reach an optimal fuel consumption pattern by adjusting the parameter range of the engine through its electric motor. There are mainly rule-based and optimisation-based strategies available in which the rule-based energy strategy uses the “CD-CS” mode [2] This means that it is better to choose the motor drive to acquire a low operating cost when the state of charge (SOC) of the power battery is good, and apply the same strategy as used in an ordinary HEV to improve the working condition of the engine and maintain the power balance when the SOC is poor [3]. Former requires an a priori understanding of the working conditions, the globally optimal solution can be acquired, it offers poor real-time performance and requires many calculations The latter weighs the fuel consumption of engine and electric consumption of the electric motor and finds the optimal mode for energy distribution, in real-time, by exploring the operating points with the lowest cost function in a feasible domain. The aforementioned multi-objective problem is transformed into a single-objective optimisation problem, which is regarded as the control objective of the instantaneous optimal control strategy
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