Integrated optimization of dedicated engine and energy management strategy for the plug-in hybrid commercial vehicle at high altitude

Abstract

To improve fuel efficiency and reduce pollutant emissions of plug-in hybrid commercial vehicles (PHCVs) at high altitude, an integrated optimization of dedicated engine of PHCV (DEP) and energy management strategy (EMS) is performed. Firstly, the physical model of DEP is established using experimental data. Its empirical model is developed through machine learning with samples generated by the physical model. Subsequently, a hybrid model-based successive approximation method is proposed to optimize various combinations of control parameters including fuel injection timing, rail pressure, VGT opening and EGR rate, aiming at reducing brake specific fuel consumption (BSFC) and NOx within the major working zone of DEP. This optimized DEP is then integrated into the PHCV model to collectively optimize EMS at this challenging altitude. Results demonstrate that this method considerably reduces optimization time without compromising model accuracy. Notably, at 4000 m altitude and under the CHTC-C driving cycle, overall BSFC reduces with a minimum of 194.27 g/(kW·h), most brake specific NOx values remain under 7.5 g/(kW·h), and optimal working range broadens. With integrated optimization, the DEP predominantly works in low-fuel consumption and low-emission zone. Consequently, the fuel economy of PHCV improves by 30.03 %, while NOx and CO2 emissions decrease by 35.88 % and 18.05 %, respectively.