Electric and hybrid propulsion systems have been developed for ground vehicles, driven by the motivation of decreasing the particle emissions from the exhaust of conventional propulsion systems. However, the more environmentally friendly fully or hybrid electric vehicles are expected to have increased non-exhaust pollution related sources compared to a conventional vehicle. A fact that could potentially cancel the benefits of removing the exhaust, due to their significantly increased mass. One of the main sources of non-exhaust pollution is the tyre wear, and can jeopardise the benefits of electrification in ground transport systems. Hence, a reformulation is required, and this is where this works lies. Inner (tyre structure and shape) and external (suspension configuration, speed, road surface, etc.) factors are mainly affecting wear, and in this work, the emphasis is given on suspension systems and more specifically on the ability of semi-active suspensions to decrease tyre wear on a hybrid vehicle. In this direction, two demo vehicles provided by IPG CARMAKER 8.0, the Demo: V olvo_X C90_T8H ybrid and Demo_Volvo_XC90_T6AWD, are considered intially to compare their tyre wear during cornering over a class C road. Then, the Demo_Volvo_XC90_T8Hybrid is employed with both comfort (SH-2, SH-ADD-2 and ADD) and road holding (PDD, SH-PDD, and GH-2) oriented semi-active suspensions to investigate the induced levels of wear. Additionally, the suspension systems are also compared with regards to other vehicle performance aspects, i.e. comfort and stability.

Lithium-ion (Li-Ion) batteries are widely used in various applications and are viable for automotive applications. The effective management of Li-Ion batteries in battery electric vehicles (BEV) plays a crucial role in performance and range. One can achieve good performance and range by using efficient battery models in battery management systems (BMS). Hence, these battery models play an essential part in the development process of battery electric vehicles. Physics-based battery models are used for design purposes, control, or to predict battery behaviour, and these require much information about materials and reaction and mass transport properties. Model parameterization, i.e., obtaining model parameters from different experimental sets (by fitting the model to experimental data sets), can be challenging depending on model complexity and the type and quality of experimental data. Based on the idea of parameter sensitivity, certain current/voltage data sets could be chosen that theoretically has a more considerable sensitivity for a given model parameter that is of interest to extract. In this thesis work, different methods for extracting model parameters for a Nickel-Manganese-Cobalt (NMC) battery composite electrode are experimentally tested and compared. Specifically, model parameterization using \emph{optimal experiments} based on performed parameter sensitivity analysis has been benchmarked against a 1C discharge test and low rate pulse tests. The different parameter sets obtained have then been validated on a drive cycle and 2C pulse tests. Comparing the methods show some promising results for the optimal experiment design (OED) method, but consideration regarding the state of charge (SOC) dependencies, the number of parameters has to be further evaluated.

Sustainability has become a very important research area in transportation where demands and associated environmental impacts have been increasing. An introductory exploration is established here, where transport efficiency is studied in two partial measures, mass efficiency and volume efficiency. An optimisation problem is then formulated here to find an acceptable design config- uration that merely satisfies the transport constraints and maximising transport efficiency. It is observed that there are trade-offs between environmental impacts in terms of energy requirement and the optimised design configuration.