Optimal energy management of hybrid electric vehicles including battery aging

The paper presents a methodology to account for battery aging in the energy management strategy for a hybrid electric vehicle. An optimal control problem is formulated to minimize fuel consumption as well as battery aging, using recently developed methods for battery lifetime modeling. The approach relies on the concept of severity factor map, a tool used to quantify the aging effects of a battery due to its different on-vehicle operating conditions. The optimal control problem is solved using Pontryagin's Minimum Principle, showing with simulations the effect of the new control approach compared to the standard energy management strategies.

[1]  Simona Onori,et al.  Lithium-ion batteries life estimation for plug-in hybrid electric vehicles , 2009, 2009 IEEE Vehicle Power and Propulsion Conference.

[2]  Hans P. Geering,et al.  Optimal control with engineering applications , 2007 .

[3]  Massoud Pedram,et al.  An analytical model for predicting the remaining battery capacity of lithium-ion batteries , 2003, 2003 Design, Automation and Test in Europe Conference and Exhibition.

[4]  Christopher D. Rahn,et al.  Model-Based Electrochemical Estimation and Constraint Management for Pulse Operation of Lithium Ion Batteries , 2010, IEEE Transactions on Control Systems Technology.

[5]  Giorgio Rizzoni,et al.  A Novel Model-Based Algorithm for Battery Prognosis , 2009 .

[6]  Simona Onori,et al.  ECMS as a realization of Pontryagin's minimum principle for HEV control , 2009, 2009 American Control Conference.

[7]  Jonathan Chauvin,et al.  Online optimal control of a parallel hybrid with costate adaptation rule , 2010 .

[8]  L. Guzzella,et al.  Control of hybrid electric vehicles , 2007, IEEE Control Systems.

[9]  L. Serrao,et al.  An aging model of Ni-MH batteries for hybrid electric vehicles , 2005, 2005 IEEE Vehicle Power and Propulsion Conference.

[10]  D. Naidu,et al.  Optimal Control Systems , 2018 .

[11]  A. Di Filippi,et al.  Model-based life estimation of Li-ion batteries in PHEVs using large scale vehicle simulations: An introductory study , 2010, 2010 IEEE Vehicle Power and Propulsion Conference.

[12]  Yann Chamaillard,et al.  On the integration of optimal energy management and thermal management of hybrid electric vehicles , 2010, 2010 IEEE Vehicle Power and Propulsion Conference.

[13]  Heinz Wenzl,et al.  Life prediction of batteries for selecting the technically most suitable and cost effective battery , 2005 .

[14]  Heinz Wenzl,et al.  Comparison of different approaches for lifetime prediction of electrochemical systems—Using lead-acid batteries as example , 2008 .

[15]  Simona Onori,et al.  Adaptive Equivalent Consumption Minimization Strategy for Hybrid Electric Vehicles , 2010 .

[16]  Alexandre Chasse,et al.  Supervisory control of hybrid powertrains: An experimental benchmark of offline optimization and online energy management , 2009 .