Application-Oriented Stochastic Energy Management for Plug-in Hybrid Electric Bus With AMT

Abstract

Taking the complex but regular characteristics of bus routines into account, the stochastic dynamic programming (SDP) might be a method with more potential to optimize the energy management of a plug-in hybrid electric bus (PHEB). However, the discrete transmission system and the continuous power system make it a complicated multidimensional optimal problem, particularly for PHEB with automated mechanical transmission (AMT), and the optimal decisions, which are obtained based on historical data, might not always well satisfy the driver's expectation to vehicle maneuverability under various driving conditions. To solve these problems, an adaptive approach based on the SDP is proposed in this paper. Exhaustively, the SDP is propelled into the input of the transmission to only optimize the torque split under the special gearshift logic, which reduces the dimensions of optimization and obtains more applicable optimal sequences. Then, an adaptive factor, which trades off the vehicle fuel economy and drivability in real time by dynamically adjusting the gearshift points and the torque split, is developed for the variation of the complicated bus driving cycles. The simulation results demonstrate that the proposed method could well respond to the variations of the driving conditions (e.g., road grade and vehicle load). Furthermore, the performance of the proposed method is discussed in detail by comparisons with different control strategies. More importantly, the proposed approach has great potential to be applied in practice.