Mrs Gordana Collier

The reliable and cost-effective operation of battery packs relies on state of power (SOP) algorithms to estimate the available power of the system. The challenges in developing these algorithms include the nonlinear behavior of batteries under high-power demands and the impact of temperature, state of charge (SOC), stack pressure and previous load history at high C-rates. This study employs analysis of variance (ANOVA) and design of experiments (DOE) to assess the impact of key factors on the power output of lithium-ion LCO pouch cells. The findings demonstrate that the effect of cell-to-cell variation on power output is more pronounced than degradation and random errors of the experiments. Further analysis shows that temperature and state of charge have a significant influence on power availability (𝑝-value

Real-time battery modelling advancements have quickly become required as the adoption of battery electric vehicles (BEVs) has rapidly increased. In this paper an open-source, improved discrete realisation algorithm, implemented in Julia for the creation and simulation of reduced-order, real-time capable physics-based models is presented. This work reduces the Doyle–Fuller–Newman electrochemical model into continuous-form transfer functions and introduces a computationally informed discrete realisation algorithm (CI-DRA) to generate the reduced-order representation. Further improvements in conventional offline model creation are obtained as well as achieving in-vehicle capable model creation for ARM-based computing architectures. Furthermore, a parametric sensitivity analysis of the presented architecture is completed as well as experimental validation of a worldwide harmonised light vehicle test procedure (WLTP) for an LG Chem. M50 21700 parameterisation. A performance comparison to a MATLAB implementation is completed showcasing a mean computational time improvement of 3.51 times for LiiBRA.jl on x86 hardware. Finally, an ARM-based implementation showcases full system model generation within three minutes for potential in-vehicle.

The object of this research was a self-resonated inverter, based on paralleled Insulated-Gate Bipolar Transistors (IGBTs), for high-frequency induction heating equipment, operating in a wide range of output powers, applicable for research and industrial purposes. For the nominal installed capacity for these types of invertors to be improved, the presented inverter with a modified circuit comprising IGBT transistors connected in parallel was explored. The suggested topology required several engineering problems to be solved: minimisation of the current mismatch amongst the paralleled transistors; a precise analysis of the dynamic and static transistors’ parameters; determination of the derating and mismatch factors necessary for a reliable design; experimental verification confirming the applicability of the suggested topology in the investigated inverter. This paper presents the design and analysis of IGBT transistors based on datasheet parameters and mathematical apparatus application. The expected current mismatch and the necessary derating factor, based on the expected mismatch in transistor parameters in a production lot, were determined. The suggested design was experimentally tested and investigated using a self-resonant inverter model in a melting crucible induction laboratory furnace.

A battery management system (BMS) design, based on linear optocouplers for Lithium-ion battery cells for automotive and stationary applications is proposed. The critical parts of a BMS are the input voltages and currents measurement circuits. In this design, they include linear optocouplers for galvanic isolation between the battery pack and the BMS. Optocouplers based on AlGaAs light emitted diodes (LED) and PIN photodiode with external operational amplifiers are used. The design features linear characteristics, to ensure the accuracy of the measurements. The suggested approach is based on graphical data digitalizing, which gives the precise values for the most sensitive parameters: photocurrent, normalized and transferred servo gain and helps the calculation procedure to be automated with MATLAB scripts. Several mathematical methods in the analysis are used in order for the necessary equations to be derived. The results are experimentally verified with prototypes.

Two robotic vehicles, ‘the leader’ and ‘the follower’ are programmed to execute ACC: the velocity of the leader robot and the distance between the robots are augmented into the robot’s state-space equation, to design the controller (MPC), which was then tuned for both velocity and distance tracking modes.

The experiment offers a novel idea on how to deliver this advanced control strategy in an applied and visual manner with laboratory experimentation supporting the theoretical aspects of learning. It brings to life some often stated theoretical qualities of an MPC controller, including quick rise time, minor fluctuation and a small distance tracking error, in line with current scientific papers. Thus, it demonstrates to students a clear correlation between theoretical expectations and real-life system performance whilst challenging their ability to work with real hardware.