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Modeling of Lithium-Ion Battery Management System and Regeneration Control Strategy for Hybrid Electric Vehicles
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 08, 2013 by SAE International in United States
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Battery management system (BMS) plays a key role in the power management of hybrid electric vehicles (HEV). It measures the state of charge (SOC), state of health (SOH) of the battery, protects the battery package and extends cells' life cycles. For HEV applications, lithium-ion battery is usually selected as electric power source due to its high specific energy, high energy density, and long life cycle. However, the non-linear characteristic of a Li-ion battery, complicated electro-chemical model, and environmental factors, raises the difficulties in the real-time estimation of the SOC for a Li-ion battery. To address this challenge, a BMS for HEVs is modeled with MATLAB/Simulink. In addition, a regenerative braking control strategy is proposed to determine the magnitude of the regenerative torque based on the battery SOC. The motor-generator system is optimized and modeled with regard to the operating time and power contribution of the e-motor during acceleration and the regeneration behavior of the generator during braking for maintaining the battery SOC within a proper range to achieve the longest battery life cycle and stable performance.
CitationZhu, Z., "Modeling of Lithium-Ion Battery Management System and Regeneration Control Strategy for Hybrid Electric Vehicles," SAE Technical Paper 2013-01-0939, 2013, https://doi.org/10.4271/2013-01-0939.
- Schouten Niels J. , Salman Mutasim A. , and Kheir Naim A. Fuzzy Logic Control for Parallel Hybrid Vehicles IEEE Transactions On Control Systems Technology 10 3 May 2002
- Gallagher , K.S. 2012 Hybrid Cars: Development & Deployment in Japan, the US, and China Historical Case Studies of Energy Technology Innovation Chapter 24, The Global Energy Assessment Grubler A. , Aguayo , F. , Gallagher , K.S. , Hekkert , M. , Jiang , K. , Mytelka , L. , Neij , L. , Nemet , G. & Wilson C. Cambridge University Press Cambridge, UK
- Plett Gregory L. Battery management system algorithms for HEV battery state-of-charge and state-of-health estimation Advanced Materials and Methods for Lithium-Ion Batteries 2007 978-81-7895-279-6
- Piller S , Perrin M , Jossen A Methods for state-of-charge determination and their applications J Power Sources 2001 96 1 113 20
- Pop , V. , Bergveld , H.J. , Notten , P.H.L. & Regtien , P.P.L. 2005 State-of-the-art of battery state-of-charge determination Measurement Science and Technology 16 12 R93 R110
- Chaturvedi Nalin A. , Klein Reinhardt , Christensen Jake , Ahmed Jasim , Kojic Aleksandar Algorithms for Advanced Battery-Management Systems IEEE Control Systems Magazine 30 3 49 68 2010
- Xu Guoqing , Li Weimin , Xu Kun , and Song Zhibin An Intelligent Regenerative Braking Strategy for Electric Vehicles Energies 2011 4 9 1461 1477 10.3390/en409 1461
- Snyder , K. , Yang , X. , and Miller , T. Hybrid Vehicle Battery Technology - The Transition From NiMH To Li-Ion SAE Technical Paper 2009-01-1385 2009 10.4271/2009-01-1385
- PNGV Battery Test Manual 3 February 2001
- Zahran M. Charge Equalization Unit for a NiCd Battery of Small Earth Observation Satellite EPS Simulation Electronics Research Institute NRC Blg., El-Tahrir St., Dokki, 12311-Giza EGYPT & Member in Space Program of National Authority for Remote Sensing and Space Science 23 Josef Tito St., Nozha, Cairo Egypt
- Yeo , H. , Kim , D.H. , Hwang , S.H Regenerative Braking Algorithm for a HEV with CVT Ratio Control During Deceleration SAE 04 CVT-41