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Aero shutter is device used for controlling air flow through front grille of the vehicle for optimal thermal and energy management. Conventionally shutters were controlled by reactive algorithm - that actuate based on reaction to powertrain cooling system response like engine coolant temperature. The predictive algorithm of aero shutter proactively actuates engine cooling fans and shutter to different positions to meet real time cooling requirement. This algorithm needs map of shutter position required for a given air flow requirement which is function of vehicle speed, fan speed, opening of another shutter (if dual shutters are used on two grilles). Deriving such map requires enormous number of simulations or wind tunnel tests at each of these parameter combinations. This paper presents Design of Experiments (DOE) studies using statistical approach to have minimal number of runs to develop such map.

This paper deals with the development of a generic approach for the thermal management of batteries used in electric vehicles. A lumped parameter model was used to determine the worst case scenario of the battery operation from thermal management standpoint. Certain driving conditions were identified as the worst load cases of battery thermal management and these driving conditions were then used to conduct on-road tests. Using the results obtained from the vehicle performance simulation and on-road tests CFD simulations were carried out to establish a relationship between the air flow requirements and the heat generated from the battery. These relations help to obtain a quick estimate of the air flow requirement to keep the battery within safe temperature limits. This methodology developed is valid for all types of batteries used in electric vehicles such as Lead Acid, Lithium Ion, Ni-MH etc.