This paper presents a model-based hybrid technique for energy management in parallel hybrid electric vehicles. This hybrid technique gives optimal solution for fuel consumption for both online and offline conditions, this technique do not need the prior knowledge of the drive cycle, its computation time, mathematical complexity and coding complexity is quite low or less. This algorithm has two parts. In the first part the modes of operations of hybrid electric vehicle is done by the help of Neural Network and IF THEN ELSE rules. In the second part the electric motor and engine combined mode 3 and charging mode 4 fuel consumption or power request is further optimized by Equivalent consumption minimization strategy (ECMS) algorithm. In this paper a hybrid technique for online condition is developed and its results are compared with ECMS only online algorithm.
Parallel hybrid electric vehicles, ECMS, neural networks, hybrid algorithm, Rule based
Vikas Gupta, Energy Management in Parallel Hybrid Electric Vehicles Combining Three Optimizing Techniques, Neural Network, Rule Based and ECMS, HCTL Open International Journal of Technology Innovations and Research (IJTIR), Volume 16, July 2015, e-ISSN: 2321-1814, ISBN: 978-1-943730-43-8.