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Simulations used to estimate carbon dioxide (CO2) emissions and fuel consumption of medium- and heavy-duty vehicles over prescribed drive cycles often employ engine fuel maps consisting of engine measurements at numerous steady-state operating conditions. However, simulating the engine in this way has limitations as engine controls become more complex, particularly when attempting to use steady-state measurements to represent transient operation. This paper explores an alternative approach to vehicle simulation that uses a “cycle average” engine map rather than a steady state engine fuel map. The map contains engine CO2 values measured on an engine dynamometer on cycles derived from vehicle drive cycles for a range of generic vehicles. A similar cycle average mapping approach is developed for a powertrain (engine and transmission) in order to show the specific CO2 improvements due to powertrain optimization that would not be recognized in other approaches.

A lumped-parameter thermal network model, based on the analogy between heat transfer and electric current flow, is presented for hybrid powertrain cooling systems. In order to optimally select the powertrain components that are commercially viable and meet performance, emission, fuel economy and life targets, it is necessary to consider the influence of cooling architecture. Especially in electric and hybrid vehicles, temperature monitoring is important to increase power and torque utilization while preventing thermal damages. Detailed thermal models such as FEA and CFD are considered for component level assessments as they can locate thermal hotspots and identify possible design changes needed. However, for the system level analysis, the detailed numerical models are not suitable due to the requirement of high computation effort.

In this work, a parallel full Hybrid Electric Vehicle (HEV) was optimized to further lower its carbon footprint without opting for any additional hardware change. The study was focused to first recognize the system efficiency of the HEV and identify its low efficiency points over the MIDC. Thereafter, different functions of the HEV were studied for their individual and cumulative contribution in the fuel economy improvement over the base non-hybrid vehicle. This, along with the low system efficiency points helped in identifying the potential areas for improvement in fuel economy. With changes in calibration and control strategies resulting in an optimal torque handling between the E-machine and the ICE, it was established through simulation and subsequent experiments conducted on chassis dynamometer, that the fuel economy of the HEV tested can be improved with the performance remaining unchanged and emissions meeting regulatory requirements.

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