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Powertrain Control development has gone through many changes in terms of process, tools and practice at all OEM's across the geography. This is mainly driven by increased number of powertrain components for control, shorter development schedules, cost control, and the need to realize the potential of electronic control to increase the performance, efficiency, safety and comfort. With the significant advancement in Powertrain Controls and additions of electronic functions, it has become imperative to automate the controller development process in the V-cycle to reduce the time and make the process more efficient while detecting any logic failures upfront at the early stage of the development cycle. Traditional practices and tools of defining the controls cannot meet new requirements. Model Based Design (MBD) approach is a promising solution to meet the critical needs of powertrain control engineering to define the control logic and validate.

In this paper, a mild hybrid system is studied for Indian drive conditions. The study is focused to first come up with detailed component sizing through simulation. Different features of mild hybrid system are studied for their individual and cumulative contribution in the fuel economy improvement over the base non-hybrid vehicle. Model based development approach has been employed to develop a supervisory control strategy for such a system. Model based design saves time and cost as it gives flexibility to the control engineer to validate the control design at an early stage of development. The supervisory control strategy is first tested in a simulated environment and then, on a vehicle. To prove the system function, a full hybrid vehicle is experimented as a mild hybrid configuration. Experiments are conducted on the test vehicle over MIDC (certification cycle) to understand the impact of mild hybridization on fuel economy and tail pipe emissions

In this study, an alternate way of development and implementation of control strategy for torque split of a Hybrid Electric Vehicle (HEV) is proposed. The control strategy evaluates each and every operating point for Internal Combustion Engine (ICE) and electric motor-generator (E-machine) corresponding to all possible torque split combinations at present time instant and finally chooses one combination with the least cost function, which is estimated by converting electrical energy into equivalent fuel consumption[2]. Henceforth, the control strategy is able to perform real time iterations to choose the E-machine and ICE torque combinations with least effective fuel consumption also referred herein to as the optimal operating points. As a result, by running the vehicle at optimal operating points, overall fuel consumption over the complete drive cycle is reduced.