NiMH battery operation analysis for hybrid

• Autorzy: Szumanowski A. , Yuhua Ch.
• Konferencja: 18; Polish-German Seminar; Development Trends in Design of Machines and Vehicles; 2006
• Języki publikacji: PL

Abstrakty

EN

This paper presents the method of determining battery state of charge according to battery modeling results. From battery modeling, electromotive force (EMF) and battery internal resistance as functions of state of charge (SOC) are obtained. The model is based on constant temperature. How temperature influences on battery performance is considered in this paper. This influence of temperature on battery performance is analyzed according to laboratory tested data and the theoretical background for calculating SOC is obtained. The algorithm of battery SOC indication is depicted in details. The algorithm of battery SOC "On-line" indication considering the influence of temperature can be easily used in practice by microprocessor.

Słowa kluczowe

EN

vehicle application; battery modelling

• Wydawca: Instytut Pojazdów Politechniki Warszawskiej
• Czasopismo: Zeszyty Naukowe Instytutu Pojazdów / Politechnika Warszawska
• Rocznik: 2006
• Tom: z. 4/63
• Strony: 103--110
• Opis fizyczny: Bibliogr. 5 poz., wykr.

Twórcy

autor

Szumanowski A.

autor

Yuhua Ch.

• Warsaw University of Technology

Bibliografia

• [1] Szumanowski A. "Fundamentals of Hybrid Vehicle Drives", Monograph Book, ISBN83-7204-114-8, Warsaw-Radom 2000.
• [2] Antoni Szumanowski, Jakub Dębicki, Arkadiusz Hajduga, Piotr Piórkowski, Chang Yu Hua, "Li-ion Battery Modeling and Monitoring Approach for Hybrid Electric Vehicle Applications", EVS-20 Los Angeles 2003.
• [3] Chang Yuhua, Piotr Piórkowski, Ewa Jankowska, "NiMH battery modeling for hybrid electric vehicle application", 2005 PELINCEC (International Conference Oct. 17-19, 2005), Warsaw, Poland.
• [4] Sabine Piller, Marion Perrin, Andreas Jossen "Methods for State-of-charge Determination and their Applications" Journal of Power Sources 96 (2001), pp. 113-120.
• [5] G. Plett "LiPB Dynamic Cell Models for Kalman-Filter SOC Estimation", EVS-20, Los Angeles.