Energy Management of Series-Parallel Hybrid Electric Vehicle Considering Engine Torque Tracking and Emissions Optimization

Due to different modes of operation, devising a near optimal energy management strategy (EMS) is quite challenging and essential for Series-Parallel Hybrid Electric Vehicle (SPHEV). In addition, The precise control of engine expected torque allocated by EMS is also an inevitable issue, which directly affects the power and stability. Restricted by different time scales between torque split optimization and engine torque control, this paper proposes a bi-level controller to improve the fuel economy, ensure power and reduce emissions of SPHEV. In the outer loop, We first formulate the energy management problem as a nonlinear and constrained optimization control problem. Three different cost functions are defined according to the operation mode, and the power distribution of the internal combustion engine (ICE) and electrical machines is solved at each sample time. In the inner loop, considering the difficulty of establishing the mechanism model of the engine system, which is caused by complexity, strong coupling and nonlinear characteristics, the engine torque control and emission optimization are solved in the framework of data-driven predictive control. The simulation is done on GT-Power and the results indicate that energy efficiency, emission performance and power are improved.