For hybrid electric vehicles (HEVs), especially for diesel-electric hybrid vehicles, the low exhaust gas temperature induced by the hybridization and fuel economy optimization will bring significant impact on the performance of the exhaust gas aftertreatment systems, and may consequently lead to violation of the tailpipe emission constraints. To investigate the influence of diesel powertrain hybridization on the aftertreatment system and tailpipe emissions, an integrated HEV model is established by incorporating the thermodynamics models of the aftertreatment systems. This comprehensive model is able to predict engine-out nitrogen oxides (NOx) concentration, exhaust gas temperature, and to describe the temperature dynamics in the aftertreatment systems. A static map of selective catalytic reduction (SCR) system temperature-dependent de-NOx efficiency is utilized, so that the tailpipe NOx can be predicted. To investigate the tradeoff between fuel consumption and emissions for diesel HEV with aftertreatment systems, a preliminary study is carried out on optimally balancing both aspects via a model predictive control scheme. This controller is designed with an explicit consideration of HEV tailpipe NOx emission constraint. The simulation results show that the HEV tailpipe NOx emissions can be regulated by slightly sacrificing the fuel economy.
- Dynamic Systems and Control Division
Model Predictive Control of Integrated Hybrid Electric Powertrains Coupled With Aftertreatment Systems
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Zhao, J, & Wang, J. "Model Predictive Control of Integrated Hybrid Electric Powertrains Coupled With Aftertreatment Systems." Proceedings of the ASME 2014 Dynamic Systems and Control Conference. Volume 2: Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing. San Antonio, Texas, USA. October 22–24, 2014. V002T36A004. ASME. https://doi.org/10.1115/DSCC2014-5999
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