• Energy Research

The paper presents use case simulations of fleets of electric buses in two cities in Europe, one with a warm Mediterranean climate and the other with a Northern European (cool temperate) climate, to compare the different climatic effects of the thermal management strategy and charging management strategy. Two bus routes are selected in each city, and the effects of their speed, elevation, and passenger profiles on the energy and thermal management strategy of vehicles are evaluated. A multi-objective optimization technique, the improved Simple Optimization technique, and a “brute-force” Monte Carlo technique were employed to determine the optimal number of chargers and charging power to minimize the total cost of operation of the fleet and the impact on the grid, while ensuring that all the buses in the fleet are able to realize their trips throughout the day and keeping the battery SoC within the constraints designated by the manufacturer. A mix of four different types of buses with different battery capacities and electric motor specifications constitute the bus fleet, and the effects that they have on charging priority are evaluated. Finally, different energy management strategies, including economy (ECO) features, such as ECO-comfort, ECO-driving, and ECO-charging, and their effects on the overall optimization are investigated. The single bus results indicate that 12 m buses have a significant battery capacity, allowing for multiple trips within their designated routes, while 18 m buses only have the battery capacity to allow for one or two trips. The fleet results for Barcelona city indicate an energy requirement of 4.42 GWh per year for a fleet of 36 buses, while for Gothenburg, the energy requirement is 5 GWh per year for a fleet of 20 buses. The higher energy requirement in Gothenburg can be attributed to the higher average velocities of the bus routes in Gothenburg, compared to those of the bus routes in Barcelona city. However, applying ECO-features can reduce the energy consumption by 15% in Barcelona city and by 40% in Gothenburg. The significant reduction in Gothenburg is due to the more effective application of the ECO-driving and ECO-charging strategies. The application of ECO-charging also reduces the average grid load by more than 10%, while shifting the charging towards non-peak hours. Finally, the optimization process results in a reduction of the total fleet energy consumption of up to 30% in Barcelona city, while in Gothenburg, the total cost of ownership of the fleet is reduced by 9%.

This paper proposes an optimal design for hybrid grid-connected Photovoltaic (PV) Battery Energy Storage Systems (BESSs). A smart grid consisting of PV generation units, stationary Energy Storage Systems (ESSs), and domestic loads develops a multi-objective optimization algorithm. The optimization aims at minimizing the Total Cost of Ownership (TCO) and the Voltage Deviation (VD) while considering the direct and indirect costs for the prosumer, and the system stability with regard to intermittent PV generation. The optimal solution for the optimization of the PV-battery system sizing with regard to economic viability and the stability of operation is found while using the Genetic Algorithm (GA) with the Pareto front. In addition, a fuzzy logic-based controller is developed to schedule the charging and discharging of batteries while considering the technical and economic aspects, such as battery State of Charge (SoC), voltage profile, and on/off-peak times to shave the consumption peaks. Thus, a hybrid approach that combines a Fuzzy Logic Controller (FLC) and the GA is developed for the optimal sizing of the combined Renewable Energy Sources (RESs) and ESSs, resulting in reductions of approximately 4% and 17% for the TCO and the VD, respectively. Furthermore, a sensitivity cost-effectiveness analysis of the complete system is conducted to highlight and assess the profitability and the high dependency of the optimal system configuration on battery prices.

This article reviews the design and evaluation of different DC-DC converter topologies for Battery Electric Vehicles (BEVs) and Plug-in Hybrid Electric Vehicles (PHEVs). The design and evaluation of these converter topologies are presented, analyzed and compared in terms of output power, component count, switching frequency, electromagnetic interference (EMI), losses, effectiveness, reliability and cost. This paper also evaluates the architecture, merits and demerits of converter topologies (AC-DC and DC-DC) for Fast Charging Stations (FCHARs). On the basis of this analysis, it has found that the Multidevice Interleaved DC-DC Bidirectional Converter (MDIBC) is the most suitable topology for high-power BEVs and PHEVs (> 10kW), thanks to its low input current ripples, low output voltage ripples, low electromagnetic interference, bidirectionality, high efficiency and high reliability. In contrast, for low-power electric vehicles (<10 kW), it is tough to recommend a single candidate that is the best in all possible aspects. However, the Sinusoidal Amplitude Converter, the Z-Source DC-DC converter and the boost DC-DC converter with resonant circuit are more suitable for low-power BEVs and PHEVs because of their soft switching, noise-free operation, low switching loss and high efficiency. Finally, this paper explores the opportunity of using wide band gap semiconductors (WBGSs) in DC-DC converters for BEVs, PHEVs and converters for FCHARs. Specifically, the future roadmap of research for WBGSs, modeling of emerging topologies and design techniques of the control system for BEV and PHEV powertrains are also presented in detail, which will certainly help researchers and solution engineers of automotive industries to select the suitable converter topology to achieve the growth of projected power density.

The wide-scale adoption and accelerated growth of electric vehicle (EV) use and increasing demand for faster charging necessitate the research and development of power electronic converters to achieve high-power, compact, and reliable EV charging solutions. Although the fast charging concept is often associated with off-board DC chargers, the importance of on-board AC fast charging is undeniable with the increasing battery capacities. This article comprehensively reviews gallium nitride (GaN) semiconductor-based bidirectional on-board charger (OBC) topologies used in both 400 V and 800 V EV applications. Moreover, comparative evaluations of GaN-based bi-directional OBC topologies regarding power conversion losses (conduction loss and soft switching capabilities), power density, implementation considerations, power quality, electromagnetic interference, and reliability aspects have been presented. The status of commercially available GaN power modules, advancements in GaN technology, applicable industry standards, and application requirements for OBCs have been also included in this study. Finally, in light of forthcoming advancements in GaN power transistor technology, this study highlights potential areas of research related to the reviewed topologies. Such research can aid researchers and designers in improving the performance and user experience of electric vehicles, ultimately supporting the widespread adoption of EVs.

Nowadays, the implementation of smart charging concepts and management strategies with vehicle-to-everything (V2X) functionalities, is required to address the increasing number of battery electric buses (BEBs) in cities. However, the introduction of these new functionalities to the charging systems might affect the lifetime of the charging infrastructure. This has not been investigated yet, although it is an important aspect for the BEB operators. Therefore, this paper performs a detailed reliability assessment to study the impact of smart and bidirectional (V2X) charging on the lifetime of SiC-based high-power off-board charging infrastructure used for BEBs in a depot for overnight charging. In this paper, four different charging current profiles, generated by a smart charging algorithm, are considered. In addition, an electro-thermal model of the charging system is developed to accurately estimate the junction temperature of the switching devices when subjected to the applied charging current profiles. The thermal stress is converted into a number of cycles to failures and accumulated damage by means of a rainflow cycle counting algorithm, a lifetime model and Miner’s damage rule. Finally, a Monte Carlo analysis and a Weibull probability function fit are applied to obtain the system reliability. The results have demonstrated that smart charging strategies can improve the lifetime of the charging system by at least a factor of three compared to conventional uncoordinated charging. Moreover, an uncoordinated charging strategy fails to fulfill the lifetime requirements in the parts per million range, while bidirectional charging could even further enhance the lifetime with a factor of one and a half.

In this article, a switched reluctance machine (SRM) with six phases and a misaligned segmental rotor is proposed. The segmental rotor has an internal 15-degree misalignment, allowing the SRM structure to be a one-layer 2D structure with a short flux path structure. The proposed SRM produces a relatively low torque ripple by exciting two phases simultaneously. Additionally, an optimization method is applied, allowing for the maximum torque position of one phase to be aligned with the zero-torque position of the adjacent phase. The finite element method (FEM) is used to analyze and design the proposed SRM and to simulate the proposed liquid cooling system. The static torque waveforms are analyzed, and the dynamic torque waveforms are simulated with a drive using SiC MOSFETs. Finally, a prototype is manufactured, and the experiment is performed to validate the design and simulation results.

This paper presents a high-fidelity electro-thermal model of a half-bridge that consists of IGBTs and anti-parallel diodes. The model calculates and estimates the half-bridge voltages, currents, switching and conduction losses considering the operating temperature and current conditions. Moreover, this model is suitable for varying switching frequency operation. The electro-thermal model can be used as an evaluation tool to analyze the performance of control strategies for traction inverter from efficiency, temperature and component stress point of view. In this paper performance of Direct Torque Model Predictive Control (DTMPC) of an Interior Permanent Magnet Synchronous Motor (IPMSM) is evaluated in comparison with Indirect Field Oriented Control (IFOC) with sinusoidal pulse width modulation (PWM). The inverter model and the MPC are both implemented in C-Mex for rapid execution. The MPC algorithm implemented in this research tracks torque reference while using Maximum-Torque-Per-Ampere (MTPA) strategy and minimizing switching losses. Both control systems are able to follow the speed reference. The MPC shows a decrease in losses compared to IFOC when tested with low-speed and high-speed parts of the WLTC profile.