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Technical Paper

Evaluation of Model Predictive and Conventional Method Based Hybrid Electric Vehicle Supervisory Controllers

2017-03-28
2017-01-1253
Increasingly strict CO2 and emissions norms are pushing the automotive industry towards increasing adoption of Hybrid Electric Vehicle (HEV) technology. HEVs are complex hardware systems which are often controlled by software that is complex to maintain, time-consuming to calibrate, and not always guaranteed to deliver optimal fuel economy. Hence, coordinated, systematic control of different subsystems of HEV is an attractive proposition. In this paper, Model Predictive Control (MPC) and Equivalent Consumption Minimization Strategy (ECMS) based supervisory controllers have been developed to coordinate the power split between the two prime movers of an HEV – internal combustion engine and electric motor. A dynamical physics based HEV model has been developed for simulation of the system behavior. A cost function has been formulated to improve fuel economy and battery life.
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