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Measuring the efficiency map of an electric machine is a complex and time-consuming process. This paper examines means for estimating the efficiency map of PM machines using a reduced number of tests. It uses a modified saturation model which gives good results even in the presence of high cross-saturation. It also models the iron loss variation with load and speed using curve fitting in the constant torque and power regions based on a limited number of load points. Both the flux-linkage and iron loss methods are applicable to finite element (FE) simulation and have the capability of being generalized to other electrical machine types. The results are verified both with FE simulation and experimental tests. Refereed/Peer-reviewed

Step-up DC-DC converters play a determinative role in traction vehicles by providing the required DC- link voltage for traction drives supplied by battery packages or fuel cells. Bi-directional converters are preferred to be used in the construction of battery-based traction drives to charge batteries when drivetrains system work in the generation mode. However, due to the fact that fuel-cells cannot be charged electrically, the bi-directional structure is not required for fuel cell-based traction drives. The proposed step up converter benefits from the resonance between its elements to provide the soft- switching condition for the converter switches. The resonance assists to transmit high power from input and to output while there is no high-frequency transformer or coupled inductor in the converter topology. In brief, the generated resonance not only leads to a high power density converter but also result in a soft-switching which means higher efficiency in comparison to previously introduced high-step up converters working in hard switching condition. So, the proposed high-efficiency high power density high step-up (HHH) converter could be employed as a reliable DC-DC converter for traction vehicles supplied by fuel cells. Refereed/Peer-reviewed

This paper presents design optimization of axialflux induction motors (AFIMs) for electric vehicles. The approach is based on an analytical resolution of the Maxwell's equations inside a set of subdomains. The analytical method is verified against 2D finite-element analysis. It allows detailed modelling and accurate steady-state performance prediction of AFIMs in a very short time (under 1sec), making possible evaluation of numerous design for the optimization. The optimization effortlessly simulates and predict the performance of various AFIM designs based on driving cycles and vehicle limitations. An optimization based on driving cycle of electric vehicles is studied through considering a driving cycle and designing minimum-mass AFIMs capable of fulfilling it. It is observed that driving-cycle based motor designs benefit from mass reduction and ensures the feasibility of all operating conditions Refereed/Peer-reviewed