Abstract
Plug-in hybrid electric buses (PHEBs) is some of the most promising products to address air pollution and the energy crisis. Considering the switching between different working modes often bring aboutsudden changes of the torque and the speed of different power sources, which may lead to the instability of the power output and affect the driving performance and ride comfort, it is of great significance to develop a real-time optimal energy management strategy for PHEBs to achieve the optimization of fuel economy and drivability. In this study, the proposed strategy includes an offline part and an online part. In the offline part, firstly, the energy conversion coefficient s(t) is optimized by linear weight particle swarm optimization algorithm (LinWPSO), then, the optimization results of s(t) are converted into a 2-dimensional look-up table. Secondly, combined with three typical driving cycle conditions, the gear-shifting correction and mode switching boundary parameters that affect the drivabilityof the vehicle are extracted by dynamic programming (DP) algorithm. In the online part, combined with the s(t), the gear-shifting correction and mode switching boundary parameters which are obtained through offline optimization, the real-time energy management strategy is proposed to solve the trade-off problem between minimizing the fuel consumption and improving the drivability and riding comfort. Finally, the proposed strategy is verified with simulation, the results show that the proposed strategy can guarantee the engine and the electric motor (EM) work in the high-efficiency area with optimal energy distribution while keeping drivability in the variation of driving circle. The overall performance is improved by 18.54% compared with the rule-based control strategy. The proposed strategy may provide theoretical support for the optimal control of PHEB.
Highlights
In recent years, new energy vehicles have developed rapidly due to the demand for energy conservation and environmental protection
It is understandable from the results that the rule-based control strategy have the worst fuel economy by using experience to set rules, the equivalent consumption minimization strategy (ECMS) takes advantage of local optimization about this driving cycle to achieve better fuel economy, whereas the adopted method considers the drivability of the vehicle to improve driving comfort at the expense of fuel consumption
A novel real-time optimal energy management strategy (EMS) based on parameter optimization for the single-shaft parallel Plug-in hybrid electric buses (PHEBs) with automated mechanical transmission (AMT) is proposed
Summary
New energy vehicles have developed rapidly due to the demand for energy conservation and environmental protection. On the basis of real-time information provided by historical driving data, mathematical models or intelligent transportation systems, MPC can predict the torque requirements of vehicles and optimize the energy allocation ratio to achieve low fuel consumption and emission [25,26]. The second part is that the corresponding control parameters that affect the vehicle drivability and riding comfort are extracted by DP algorithm, which includes AMT gear-shifting strategy and mode switching boundary parameters. In the online part, combining with the s(t), AMT gear-shifting correction and mode switching boundary parameters which are obtained through offline optimization, the real-time EMS is proposed to solve the trade-off problem between minimizing the fuel consumption and improving the drivability and ride comfort.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
