A robust non-linear observer is proposed to estimate the state of charge (SoC) of a lithium-ion battery by employing an electrical model of the battery. Considering the non-linear behaviour of the open circuit voltage versus SoC curve, a non-linear state space model is established. The modelling errors and uncertainties are compensated by the proposed non-linear observer resulting in robustness in the presence of these errors, which is the main feature of the proposed observer. The stability of the observer is proved by the Lyapunov criteria. The effectiveness of the proposed observer is verified by using the experimental test. The test results show that the proposed approach is effective and estimates the SoC with high accuracy. Additional experimental test verifies the robust performance of the proposed observer in the presence of the modelling errors and disturbances.

Despite the yearly rise in the market quota of full electric vehicles, the main limitations on the deployment of electric vehicles are the real performances of the battery storage during operation. In this study, the authors focus on hybrid electrical storage systems composed of lead acid batteries and supercapacitors. Two different coupling methods are investigated: (i) the direct parallel coupling of the two storage devices and (ii) coupling by means of a step-up converter between the supercapacitor bank and direct current (DC) link of the entire power-train, where lead acid batteries are also connected. A specific control strategy is proposed and implemented in the step-up converter to guarantee the correct power management of the power train and in particular: (i) to save the power request to the lead acid battery pack, (ii) maintain an adequate state of charge of the supercapacitor bank, and (iii) guarantee an adequate voltage level on the DC link. A prototype of the hybrid battery, integrating the proposed control technique, was realised and tested on a real forklift. The performances of the entire power-train were experimentally measured in a warehouse test cycle emulating a typical daily working cycle.

Utilisation of renewable energy sources (RES) is increasing day by day to reduce greenhouse emissions. The toxic emission from ship is the main concern in marine sector. Here, utilisation of renewable energy for propulsion and electrification of accessories in a ship are proposed. Microgrid with AC and DC bus is developed using solar panels, wind mills, fuel cell, diesel generator, and energy storage devices. Energy management system with two fuzzy logic controllers (FLCs) is used to select and manage energy in the microgrid. Selection of source is decided by FLC1 based on the availability of RES. Generation of control pulses for inter-linking converters is decided by FLC2 based on variation in solar irradiance and wind velocity. The microgrid with RES is simulated using MATLAB/SIMULINK. The results show that uncertainty in RES can be handled by FLCs to provide a continuous power supply for transportation of ship and its accessories.

The performance requirement of a squirrel cage induction motor (IM) for application in electric vehicle (EV), with high efficiency, power factor and breakdown torque, is a challenging task for a machine designer. A new 5 hp wide speed operating range IM suitable for EV application has been designed here. The parametric study to analyse the effect of stator and rotor slot dimensions on different performance parameters has been carried out. This parametric study forms the basis of the multi-objective optimisation problem taken in this study. An evolutionary algorithm has been used for the IM design optimisation and its performance is compared to that of a conventional one. The optimised IM is then fabricated and tested in the laboratory to validate the simulation results.