This paper provides a comprehensive overview of recent advancements in autonomous electric vehicles (AEV) within the specified region. It elaborates on the progress and comparative analysis of diverse subsystems, including energy storage, cell balancing for battery systems, vehicle charger layouts, electric vehicle motor mechanisms, and braking systems. Furthermore, this paper showcases several prototype autonomous electric vehicles as conclusive study findings.
This article introduces a new Electrochemical-Polarization System (EPS) Model to improve lithium-ion battery models for autonomous electric vehicles (AEVs). The model incorporates an additional RC network to capture the relaxation effect in these batteries. The Nernst model is used to express the open-circuit voltage as a function of State of Charge (SoC), eliminating the need for time-consuming tests. Model parameters are estimated using the least squares method with data from a hybrid power pulse characteristic test. Experimental results validate the accurate simulation of battery behavior over time. Implementing this model and parameter determination approach eliminates the need for laborious tests traditionally used for parameter calibration.
Unlike the United States, Nigeria's installed overall electricity capacity is 12.8 GW, while the operational capacity is estimated to be 3.9 GW which is well below the current demand of 98 GW. This results in a consumer power demand shortfall of 94.1 GW across the country. As a result of this wide gap between demand and generation, only about 45% of Nigeria's citizens have access to electricity. In this paper, a comparative feasibility analysis of the utilization of a photovoltaic system with energy storage for residential application is presented. The comparative analysis is conducted to compare the feasibility of using a solar Farm with an energy storage system between the US and Nigeria. This analysis is carried out using a model developed by IREQ Hydro-Quebec Research Institute. The results are shown in phasor form to analyze the energy stored, solar intensity, and also enable the community in making informed decisions regarding reducing grid dependency.