A Fuzzy Based Safe Power Management Algorithm for Energy Storage Systems in Electric Vehicles

Electric and hybrid vehicles (EVs & HEVs) can offer a sensible improvement of the overall vehicle environmental impact, achieving at the same time a more efficient energy use. Nevertheless, these objectives can be reached only in presence of a widespread of these technologies. Today one of the most important elements which slacken the spreading of the EVs & HEVs is the gap between the costs and the performances of the conventional cars and of those based on electric propulsion. In particular, the scanty autonomy of the electric vehicles is one of the main problems which the engineers must deal with. As the autonomy problem can be solved by a suitable battery management system, in this paper a fuzzy based safe power management system for EVs is proposed. Some computer simulations confirmed the effectiveness of the proposed system allowing an improvement of vehicle's autonomy with only a moderate degradation of performances in terms of speed and acceleration

[1]  P. Siano,et al.  Extended Fuzzy C-Means and Genetic Algorithms to Optimize Power Flow Management in Hybrid Electric Vehicles , 2003, Proceedings of 2003 IEEE Conference on Control Applications, 2003. CCA 2003..

[2]  Hao Ying,et al.  Fuzzy control to improve high-voltage battery power and engine speed control in a hybrid electric vehicle , 2005, NAFIPS 2005 - 2005 Annual Meeting of the North American Fuzzy Information Processing Society.

[3]  K. B. Wipke,et al.  ADVISOR 2.1: a user-friendly advanced powertrain simulation using a combined backward/forward approach , 1999 .

[4]  Keith Wipke,et al.  ANALYSIS OF THE FUEL ECONOMY BENEFIT OF DRIVETRAIN HYBRIDIZATION , 1997 .

[5]  E. Hannah Book reviews - A history of engineering and science in the bell system, National service in war and peace , 1981, IEEE Control Systems Magazine.

[6]  S Poorani,et al.  Intelligent controller design for electric vehicle , 2003, The 57th IEEE Semiannual Vehicular Technology Conference, 2003. VTC 2003-Spring..

[7]  E. Czogala,et al.  Automatic tool selection using a fuzzy decision support system , 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..

[8]  Pierluigi Siano,et al.  Fuzzy Clustering applied to power flow management for Parallel Hybrid Electric Vehicles , 2002 .

[9]  R. P. Jones,et al.  Energy management in an automotive electric/heat engine hybrid powertrain using fuzzy decision making , 1993, Proceedings of 8th IEEE International Symposium on Intelligent Control.

[10]  Alfredo Vaccaro,et al.  A genetic-based methodology for hybrid electric vehicles sizing , 2001, Soft Comput..

[11]  Lotfi A. Zadeh,et al.  Fuzzy logic = computing with words , 1996, IEEE Trans. Fuzzy Syst..

[12]  Keith Wipke,et al.  HEV Control Strategy for Real-Time Optimization of Fuel Economy and Emissions , 2000 .

[13]  Mutasim A. Salman,et al.  Fuzzy logic control for parallel hybrid vehicles , 2002, IEEE Trans. Control. Syst. Technol..

[14]  Pierluigi Siano,et al.  Agent-based architecture for designing hybrid control systems , 2006, Inf. Sci..

[15]  Fuzzy Logic in Control Systems : Fuzzy Logic , 2022 .

[16]  A. Piccolo,et al.  Optimisation of energy flow management in hybrid electric vehicles via genetic algorithms , 2001, 2001 IEEE/ASME International Conference on Advanced Intelligent Mechatronics. Proceedings (Cat. No.01TH8556).

[17]  Chuen-Chien Lee FUZZY LOGIC CONTROL SYSTEMS: FUZZY LOGIC CONTROLLER - PART I , 1990 .

[18]  W. C. Morchin Energy management in hybrid electric vehicles , 1998, 17th DASC. AIAA/IEEE/SAE. Digital Avionics Systems Conference. Proceedings (Cat. No.98CH36267).