Abstract
The Energy Management System developed for the hybrid electric vehicle operates using a database with GPS co-ordinates and corresponding altitudes mapped, thereby giving a predictive control to optimize the operation of the series–parallel hybrid system. The system aims at extracting the maximum potential of the series–parallel hybrid power train architecture. The mapping of the latitude and longitude obtained from a global positioning system (GPS) to the altitude measured to create a database which generates a predefined driving cycle prior to the actual motion of the vehicle. The created database is then used in a MATLAB/Simulink model to simulate the operation of the series–parallel hybrid system and implement the Energy Management System. The validated data is then tested in a Raspberry Pi (RPi)-based prototype. The Energy Management System regulates the vehicle dynamics based on the input drive cycle. The fuzzy logic-based control mechanism is implemented in the RPi to optimize the load sharing between the IC engine and the brushless DC motor.
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Acknowledgements
We are thankful to E-Mobility Research & Development Center at Faculty of Engineering, CHRIST (Deemed to be University), Bengaluru, for the facilities provided in the development of this project.
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Thomas, J., Thomas, A., Biju, A., Mathew, A., Jose, C.P., Haneesh, K.M. (2020). A GPS-Gradient Mapped Database-Based Fuzzy Energy Management System for a Series—Parallel Hybrid Electric Vehicle. In: Pradhan, G., Morris, S., Nayak, N. (eds) Advances in Electrical Control and Signal Systems. Lecture Notes in Electrical Engineering, vol 665. Springer, Singapore. https://doi.org/10.1007/978-981-15-5262-5_38
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DOI: https://doi.org/10.1007/978-981-15-5262-5_38
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