Leveraging the benefits of ethanol-fueled advanced combustion and supervisory control optimization in hybrid biofuel-electric vehicles

The advanced combustion-based dedicated hybrid engines (DHEs) operating with biofuels demonstrate great advantages to reduce greenhouse gas emissions. To explore the potential of this solution, the synergistic effect of bio-ethanol and spark-induced compression ignition (SICI) combustion with reliance on efficient supervisory control systems is evaluated for greenhouse gas (GHG) emission reduction. This article is pioneered with the forward engineering of SICI combustion engine for plug-in hybrid biofuel-electric vehicles (PHBEVs) by optimizing the high-efficiency region of SICI combustion system for the PHBEV with dynamic programming (DP)based case studies, after which the DHE prototype is produced using one-dimension and three-dimension engine digital twin models. Further, experimental test data of the optimized DHE is used to model the PHBEV in GTSuite and MATLAB/Simulink software, and its charge-sustaining (CS) performance with rule-based control and adaptive equivalent minimization control strategy (A-ECMS) under both homologation and real-world driving cycles is evaluated and compared with the offline DP. The results show that the SICI combustion engine-based PHBEV with ethanol blending from E20 to E100 can reduce the well-to-wheel (WTW) CO2 emissions by 28% to 75%, respectively, where more than 7% of the reduction is contributed by control system optimization using A-ECMS. Moreover, the digital twin-based simulation platform developed in this work can be applied to evaluate and optimize the advanced combustion engines and supervisory controllers for hybrid biofuel-electric vehicles.

Automated summary

The article investigates the potential of advanced combustion-based dedicated hybrid engines for reducing greenhouse gas emissions in biofuel-electric vehicles. It presents a methodology for optimizing the combustion system and control system, and evaluates the performance of the optimized engine under different driving cycles. The results show a significant reduction in CO2 emissions, and a digital twin-based simulation platform is developed for further evaluation and optimization.