Energy Management of Hybrid Vehicle using Artificial Intelligence for Optimal Fuel Efficiency
S.L. Badjate1, Zoonubiya Khan Ali2, R.V Kshirsagar3

1Dr. S.L. Badjate, Principal, S. B. Jain Institute of Technology, Management & Research, Nagpur (M.S.), India.
2Zoonubiya Khan Ali, Assistant Professor, Department of Electronics & Telecommunication Engineering, Disha Institute of Management and Technology, Raipur (C.G.), India.
3Dr. R.V Kshirsagar, Principal, Priyadarshini Indira Gandhi College of Engineering, Nagpur (M.S.), India.

Manuscript received on May 12, 2016. | Revised Manuscript received on May 18, 2016. | Manuscript published on July 05, 2016. | PP: 31-36 | Volume-6 Issue-3, July 2016. | Retrieval Number: C2868076316
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Abstract: In general, hybrid systems can be commanded by splitting the required power between the electric machine and ICE to meet the specific needs like fuel consumption, efficiency, performance, and emissions. This power splitting scenario, which is the key point of hybridization, is in fact the control strategy or energy management of the hybrid automobile. Performance of the system, therefore, depends on the control strategy which needs to be robust (independent from uncertainties and always be stable) and reliable. Moreover, in order to improve the system, the control strategy should be adaptive to track the demand changes from the driver or drive cycle for optimization purposes. In order to fulfill these conditions, there is a need to develop an efficient control strategy, which can split power based on demands of the driver and driving conditions. Hence, for optimal energy management of PHEV, interpretation of driver command and driving situation is most important. In view of this, a fuzzy logic based strategy for interpretation of driver command is proposed in this paper.
Keywords: Hybrid vehicles, fuzzy logic, driver command, parallel hybrid vehicles.