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Most of the present electric vehicle (EV) on-board chargers utilize a conventional design, i.e., a boost-type Power Factor Correction (PFC) controller followed by an isolated DC/DC converter. Such design usually yields a ~94% wall-to-battery efficiency and 2~3kW/L power density at most, which makes a high-power charger, e.g., 20kW module difficult to fit in the vehicle. As described in this paper, first, an E-mode GaN HEMT based 7.2kW single-phase charger was built. Connecting three such modules to the three-phase grid allows a three-phase >20kW charger to be built, which compared to the conventional three-phase charger, saves the bulky DC-bus capacitor by using the indirect matrix converter topology. To push the efficiency and power density to the limit, comprehensive optimization is processed to optimize the single-phase module through incorporating the GaN HEMT switching performance and securing its zero-voltage switching.

Fuel cell based powertrains are considered as potential candidates for future vehicles. Modeling of vehicle powertrains, using a combination of components and energy storage media, are widely used to predict vehicle performances under different duty cycles. This paper deals with performance analysis of a light-duty vehicle comprised of a PEM fuel cell stack, in combination with different energy storage systems using Powertrain Simulation Analysis Toolkit (PSAT). The performance of the stack was characterized by experimental data on a smaller PEM stack and was used in the simulation. The stack data was collected at controlled loading and thermal parameters. Three energy storage systems are considered in the analysis: nickel metal hydride battery storage, lithium-ion battery storage and ultra capacitor energy storage. The simulation results were analyzed for comparative evaluations and to optimize the performance of the fuel cell powertrain configurations.

This paper begins with a baseline multi-objective optimization problem for the lithium-ion battery cell. Maximizing the energy per unit separator area and minimizing the mass per unit separator area are considered as the objectives when the thickness and the porosity of the positive electrode are chosen as design variables in the baseline problem. By employing a reaction zone model of a Graphite/Iron Phosphate Lithium-ion Cell and the Genetic Algorithm, it is shown the shape of the Pareto optimal front for the formulated optimization takes a convex form. The identified shape of the Pareto optimal front is expected to guide Design of Experiments (DOE) and product design. Compared with the conventional studies whose optimizations are based on a single objective of maximizing the specific energy, the proposed multi-objective optimization approach offers more flexibility to the product designers when trade-off between conflicting objectives is required.