Energy storage system (ESS) technology is still the logjam for the electric vehicle (EV) industry. Lithium-ion (Li-ion) batteries have attracted considerable attention in the EV industry owing to their high energy density, lifespan, nominal voltage, power density, and cost. In EVs, a smart battery management system (BMS) is one of the essential components; it not only measures the states of battery accurately, but also ensures safe operation and prolongs the battery life. The accurate estimation of the state of charge (SOC) of a Li-ion battery is a very challenging task because the Li-ion battery is a highly time variant, non-linear, and complex electrochemical system. This paper explains the workings of a Li-ion battery, provides the main features of a smart BMS, and comprehensively reviews its SOC estimation methods. These SOC estimation methods have been classified into four main categories depending on their nature. A critical explanation, including their merits, limitations, and their estimation errors from other studies, is provided. Some recommendations depending on the development of technology are suggested to improve the online estimation.

The energy storage system (ESS) is the main issue in traction applications, such as battery electric vehicles (BEVs). To alleviate the shortage of power density in BEVs, a hybrid energy storage system (HESS) can be used as an alternative ESS. HESS has the dynamic features of the battery and a supercapacitor (SC), and it requires an intelligent energy management system (EMS) to operate it effectively. In this study, a real-time EMS is proposed, which is comprised of a fuzzy logic controller-based low-pass filter and an adaptive proportional integrator-based charge controller. The proposed EMS intelligently distributes the required power from the battery and SC during acceleration. It allocates the braking energy to the SC on the basis of the state of charge. A simulation study was conducted for three standard drive cycles (New York City cycle, Artemis urban cycle, and New York composite cycle) using MATLAB Simulink. Comparative analysis of conventional and proposed EMSs was carried out. The results reveal that the proposed EMS reduced the stress, temperature, and power losses of the battery. The steady-state charging performance of the SC was 98%, 95%, and 96% for the mentioned drive cycles.

Home Energy Management Systems (HEMSs) may not be able to solve network issues, especially in the presence of high penetration level of Electric Vehicles (EVs) and decentral renewable energy. To solve the problem, Grid Energy Management Systems (GEMSs) were introduced. However, because of the contradictory nature of the main objectives of HEMS which are economical oriented on end-users, e.g., cost minimization, and GEMS which are technical oriented on system operators, e.g., maximization of system stability and power quality cannot be satisfied simultaneously. Hence, a multi-level energy management system seems to be necessary to improve the techno-economic performance of the distribution system while satisfying end-users, electricity retailers, and the system operator. Because of the significance of the subject, this paper presents the state-of-the-art regarding different energy management systems at home, aggregator, and network levels. The advantages and disadvantages of each system are discussed and compared, considering their main elements such as objective functions, constraints, optimization algorithms, communication protocols, and impact of EVs. The challenges and limitations in hierarchical energy management are explained. Finally, some future research directions are suggested to improve the multi-level energy management system.

The electric powered wheelchair (EPW) is an essential assistive tool for people with serious injuries or disability. This manuscript describes the validation of applied research for reducing the charging time of an electric wheelchair using a hybrid electric system (HES) composed of a supercapacitor (SC) bank and a lithium-ion battery with a fuzzy logic controller (FLC)-based fast charging system for Li-ion batteries and a fuzzy logic-based intelligent energy management system (FLIEMS) for controlling the power flow within the HES. The fast charging FLC was designed to drive the voltage difference (V_d) among the different cells of a multi-cell battery and the cell voltage (V_c) of an individual cell. These parameters (voltage difference and cell voltage) were used as input voltages to reduce the charge time and activate a bypass equalization (BPE) scheme. BPE was introduced in this paper so that the battery operates within the safe voltage range. For SC/Li-ion HES, the FLIEMS presented in this paper controls the bi-directional power flow to smooth the power extracted from Li-ion batteries. Moreover, a dual active bridge isolated bidirectional DC converter (DAB-IBDC) was used for power conversion. The DAB-IBDC presented in this paper has the characteristics of galvanic isolation, and high power conversion efficiency compared to the conventional converter circuits due to the reduced reverse power flow and current stresses.

Transit agencies are increasingly embracing electric buses (EB) as an energy-efficient and emission-free alternative to the conventional bus fleets. They are rapidly replacing conventional buses with electric ones. As a result, emerging challenges of electrifying public transportation bus networks in cities should be addressed. Introducing electric buses to the bus transit system would affect the public transit operation planning steps. The steps are network design, timetabling, bus scheduling, and crew scheduling. Regarding the functional and operational differences between conventional buses and electric buses, such stages should be changed and optimized to enhance the level of service for the users while reducing operating costs for service providers. Many mathematical optimization models have been developed for conventional buses. However, such models would not fit the electric buses due to EBs’ limited traveling range and long charging time. Therefore, new mathematical models should be developed to consider the unique features of electric buses. We present a comprehensive literature review to critically review and classify the work done on these topics. This paper compares the studies that have been done in this field and highlight the missing links and gaps in the considered papers, and the potential future studies that could be done. The considered papers cover the integration of timetabling and vehicle scheduling, recharging scheduling planning, and fast charging infrastructure location planning and its impacts on the grid. The main goal of this research is to highlight the research gaps and potential directions for future studies in this domain to encourage more realistic and applicable models and solution approaches for fully electric bus transit systems.