Intensive development of hybrid electric vehicles in recent years is conditioned by ecological requirements reflecting in the reduction of greenhouse gas emission and by the limitation of the use of fossil fuel. Lithium-Ion Batteries (LIBs) become unavoidable component serving as an energy storage element in transportation industry as well as in solar and wind energy systems. The problems related to battery state monitoring in hybrid electric vehicles refer to the estimation of immeasurable degradation parameters. Concerning existing literature, the measurements indirectly correlated to the deterioration process are used for the calculation of degradation parameters. Special attention is given to LIB parameters related to battery aging such as capacity fade and internal resistance increase. Existing approaches to these parameters estimation/calculation concern no direct measurement of degradation parameters. Indirect relations can be established assuming suitable assumptions. The contribution addresses the main issues related to LIB parameters monitoring as well as to the adopted control strategy providing high energy efficiency while maintaining as less as possible rate of component degradation.
- Dynamic Systems and Control Division
Li-O Battery Aging Process: A Comprehensive Review With Respect to the Integration of Aging Into System’s Powermanagement
Beganovic, N, Moulik, B, & Söffker, D. "Li-O Battery Aging Process: A Comprehensive Review With Respect to the Integration of Aging Into System’s Powermanagement." Proceedings of the ASME 2015 Dynamic Systems and Control Conference. Volume 1: Adaptive and Intelligent Systems Control; Advances in Control Design Methods; Advances in Non-Linear and Optimal Control; Advances in Robotics; Advances in Wind Energy Systems; Aerospace Applications; Aerospace Power Optimization; Assistive Robotics; Automotive 2: Hybrid Electric Vehicles; Automotive 3: Internal Combustion Engines; Automotive Engine Control; Battery Management; Bio Engineering Applications; Biomed and Neural Systems; Connected Vehicles; Control of Robotic Systems. Columbus, Ohio, USA. October 28–30, 2015. V001T13A004. ASME. https://doi.org/10.1115/DSCC2015-9759
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