Comprehensive powertrain modeling for heavy-duty applications: A study of plug-in hybrid electric bus. (15th January 2022)

• Record Type: Journal Article
• Authors: Gao, Zhiming; LaClair, Tim J.; Nawaz, Kashif; Wu, Guoyuan; Hao, Peng; Boriboonsomsin, Kanok; Todd, Mike; Barth, Matt; Goodarzi, Abas
• Is Part Of: Energy conversion and management. Volume 252(2022)
• Publication Date: 2022-01-15
• Subjects: Powertrain modeling -- Forward-looking -- Control strategy -- Hybrid electric bus -- Eco-driving; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2021.115071
• Languages: English
• ISSNs: 0196-8904

Abstract

Graphical abstract: Highlights: A comprehensive model is developed to optimize PHEB powertrain efficiency. The powertrain control algorithm includes charge- and discharge-dominant controls. A CEED database enables rapid selection of an optimal powertrain operating state. Energy savings by the control strategy were 10%–30% compared with the baseline HEV. The powertrain control algorithm has been implemented into a prototype hybrid bus. Abstract: A comprehensive forward-looking powertrain model with an efficiency-based control strategy was developed to achieve real-time optimization of plug-in hybrid electric buses while considering the real vehicle drivability and the practical operation of all powertrain components under real driving conditions. The control strategy is based on a supervisory control algorithm that alternately employs charge-dominant control and discharge-dominant control to manage multiple powertrain sources, and enable an optimal overall efficiency-based powertrain operation state by maximizing the inherent optimal powertrain efficiency through best all transmission gear choice and the blend of motor and/or engine power. In the model, a component energy efficiency database was developed to rapidly enable an smart and optimal operating state determined from a set of efficiency maps characterizing the component and powertrain control states as a function of the instantaneous vehicle operational condition. The results revealed that the energy savings achieved with the innovative powertrain control improved by 10%–30% compared with the baseline hybrid powertrain control strategy. The benefits of eco-driving with respect to energy consumption were also evaluated using the powertrain model. The powertrain control model was implemented into a real hybrid bus. Measured energy savings with the optimized control strategy were similar to the simulated results.