Anand Ganesan, S. Gros, Nikolce Murgovski, Chih Feng Lee, M. Sivertsson
{"title":"Effect of Engine Dynamics on Optimal Power-Split Control Strategies in Hybrid Electric Vehicles","authors":"Anand Ganesan, S. Gros, Nikolce Murgovski, Chih Feng Lee, M. Sivertsson","doi":"10.1109/VPPC49601.2020.9330841","DOIUrl":null,"url":null,"abstract":"This paper presents a model predictive control (MPC) based supervisory power-split control strategy, which optimises fuel and energy consumption in Hybrid Electric Vehicles (HEVs) by incorporating powertrain actuator dynamic models. In HEVs, while distributing the driver demand to the powertrain actuators, a standard approach is to approximate the actuator energy conversion dynamics with steady-state maps, which leads to sub-optimal control policy and increased fuel & energy consumption, especially for a driving mission with high transient demands. To address this shortfall, the control strategy proposed in this paper explicitly integrates an experimentally validated dynamic model of gasoline internal combustion engine (ICE) into an MPC based power-split controller. The proposed strategy is validated in a parallel HEV platform, where the sensitivity of the HEV energy consumption w.r.t. its actuator dynamics and the transients in its load demands, is also established. The results enable an understanding of the energy saving potential in HEVs that supports the inclusion of actuator dynamic models in optimal power-split controllers and it also establishes that the proposed control strategy realises higher energy and fuel savings in HEVs.","PeriodicalId":6851,"journal":{"name":"2020 IEEE Vehicle Power and Propulsion Conference (VPPC)","volume":"17 1","pages":"1-8"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Vehicle Power and Propulsion Conference (VPPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VPPC49601.2020.9330841","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper presents a model predictive control (MPC) based supervisory power-split control strategy, which optimises fuel and energy consumption in Hybrid Electric Vehicles (HEVs) by incorporating powertrain actuator dynamic models. In HEVs, while distributing the driver demand to the powertrain actuators, a standard approach is to approximate the actuator energy conversion dynamics with steady-state maps, which leads to sub-optimal control policy and increased fuel & energy consumption, especially for a driving mission with high transient demands. To address this shortfall, the control strategy proposed in this paper explicitly integrates an experimentally validated dynamic model of gasoline internal combustion engine (ICE) into an MPC based power-split controller. The proposed strategy is validated in a parallel HEV platform, where the sensitivity of the HEV energy consumption w.r.t. its actuator dynamics and the transients in its load demands, is also established. The results enable an understanding of the energy saving potential in HEVs that supports the inclusion of actuator dynamic models in optimal power-split controllers and it also establishes that the proposed control strategy realises higher energy and fuel savings in HEVs.