Optimal Control Strategy Using Cloud for a Parallel Topology Based HEV to Minimize Energy Consumption

Two-wheelers especially scooters constitute a majority market share in Asian countries. A hybrid drive-train integration of electric motor/motors with a conventional IC engine is a suitable solution to achieve reduction in CO2 emissions and as an alternative to IC Engine only vehicles. A model based supervisory controller is proposed, considering the behavior of the electrical drive, IC engine as well as the transmission, which determines the modes of operation. The controller determines the commanded torque split between the engine and electric motor across all modes of operations. With the information about the driving cycle, an optimal controller based on dynamic programming that minimizes fuel and equivalent electrical energy consumption with charge sustaining feature is proposed. This supervisory controller was simulated for hybrid configuration running on WMTC driving cycle to minimize equivalent energy consumption. The performance of the proposed controller with hybrid powertrain is compared against a conventional powertrain. Cloud Computing is gaining force as it acts as an online fast computing platform enabling scalability, online resource management, seamless integration with hardware along with the most important benefit of reduced computation requirements at the edge. This supervisory controller was hence also implemented on a Cloud Service platform.