During the assembly process of battery packs for electric vehicles, it is crucial to ensure that the cell-to-busbar joints can be produced with high quality, good reliability, and with minimal impact on the individual battery cells. This thesis project investigates the influence of different process parameters on the joint quality for laser welded dissimilar material cell-to-busbar joints. Nickel plated copper and steel plates, joined in an overlap configuration, are used as a simplified geometry, representing a cell-to-busbar joint. By the utilization of artificial neural network-based meta models, trained on numerical results from computational fluid dynamics simulations of the laser welding process, the joint quality is predicted and evaluated. The present thesis investigates how a set of optimized process parameters can be identified for the considered laser welded dissimilar material cell-to-busbar joints, in order to simultaneously maximize the interface width for the joints, and minimize the formation of undercuts and resulting in-process temperatures. NSGA-II is used to efficiently search for trade-off solutions, in an meta model-based multi-objective optimization approach, where the meta models are used to approximate the objectives, corresponding to the joint quality obtained from computational fluid dynamics simulations. With this, the time for one objective evaluation is reduced from approximately 9 hours, when the objectives are evaluated directly from computational fluid dynamics simulations, to only tenths of a second. With the proposed optimization approach, the Pareto-optimal front of trade-off solutions is identified, leading to the selection of three optimal solutions for validation. The validity of the proposed optimization approach, and the selected optimal solutions, are confirmed by means of both physical laser welding experiments and computational fluid dynamics simulations. It is shown that the selected optimal solutions, corresponding to three parameter setups, can be used to produce joints with large interface width and low in-process temperatures, without achieving a full penetration in the lower plate of the joint.

This thesis develops dynamic models for the two-mode FWD EVT, develops a control system based on those models that is capable of meeting driver torque demands and performing synchronous mode shifts between different EVT modes while also accommodating preferred engine operating points. The two-input two-output transmission controller proposed herein incorporates motor-generator dynamics, is based on a general state-space integral control structure, and has feedback gains determined using linear quadratic regulator (LQR) optimization. Dynamic modeling of the vehicle is categorized as dynamic modeling of the mechanical and electrical subsystems where the mechanical subsystem consists of the planetary gear sets, the transmission and the engine whereas the electrical subsystem consists of the motor-generator units and the battery pack. A discussion of load torque is also considered as part of the mechanical subsystem. With the help of these derived dynamic models, a distinction is made between dynamic output torque and steady-state output torque. The overall control system consisting of multiple subsystems such as the human driver, power management unit (PMU), friction brakes, combustion engine, transmission control unit (TCU) and motor-generator units is designed. The logic for synchronous mode shifts between different EVT modes is also detailed as part of the control system design. Finally, the thesis presents results for responses in individual operating modes, EVT mode shifting and a full UDDS drive cycle simulation.