Geometric-Process-Based Battery Management Optimizing Policy for the Electric Bus

With the rapid development of the electric vehicle industry and promotive policies worldwide, the electric bus (E-bus) has been adopted in many major cities around the world. One of the most important factors that restrain the widespread application of the E-bus is the high operating cost due to the deficient battery management. This paper proposes a geometric-process-based (GP-based) battery management optimizing policy which aims to minimize the average cost of the operation on the premise of meeting the required sufficient battery availability. Considering the deterioration of the battery after repeated charging and discharging, this paper constructs the model of the operation of the E-bus battery as a geometric process, and the premaintenance time has been considered with the failure repairment time to enhance the GP-based battery operation model considering the battery cannot be as good as new after the two processes. The computer simulation is carried out by adopting the proposed optimizing policy, and the result verifies the effectiveness of the policy, denoting its significant performance on the application of the E-bus battery management

Optimal Strategy to Exploit the Flexibility of an Electric Vehicle Charging Station

The increasing use of electric vehicles connected to the power grid gives rise to challenges in the vehicle charging coordination, cost management, and provision of potential services to the grid. Scheduling of the power in an electric vehicle charging station is a quite challenging task, considering time-variant prices, customers with different charging time preferences, and the impact on the grid operations. The latter aspect can be addressed by exploiting the vehicle charging flexibility. In this article, a specific definition of flexibility to be used for an electric vehicle charging station is provided. Two optimal charging strategies are then proposed and evaluated, with the purpose of determining which strategy can offer spinning reserve services to the electrical grid, reducing at the same time the operation costs of the charging station. These strategies are based on a novel formulation of an economic model predictive control algorithm, aimed at minimising the charging station operation cost, and on a novel formulation of the flexibility capacity maximisation, while reducing the operation costs. These formulations incorporate the uncertainty in the arrival time and state of charge of the electric vehicles at their arrival. Both strategies lead to a considerable reduction of the costs with respect to a simple minimum time charging strategy, taken as the benchmark. In particular, the strategy that also accounts for flexibility maximisation emerges as a new tool for maintaining the grid balance giving cost savings to the charging stations

Overview of Main Electric Subsystems of Zero-Emission Vehicles

The rapid growth of the electric vehicle market has stimulated the attention of power electronics and electric machine experts in order to find increasingly efficient solutions to the demands of this application. The constraints of space, weight, reliability, performance, and autonomy for the power train of the electric vehicle (EV) have increased the attention of scientific research in order to find more and more appropriate technological solutions. In this chapter, it proposes a focus on the main subsystems that make a zero-emission vehicle (ZEV), examining current features and topological configurations proposed in the literature. This analysis is preliminary to the various electric vehicle architectures proposed in the final paragraph. In particular, the electric drive represents the core of the electric vehicle propulsion. It is realized by different subsystems that have a single mission: ensure the requested power/energy based on the operating condition. Particular attention will be devoted to power subsystems, which are the fundamental elements to improving the performance of the ZEV

New Perspectives on Electric Vehicles

Modern transportation systems have adverse effects on the climate, emitting greenhouse gases and polluting the air. As such, new modes of non-polluting transportation, including electric vehicles and plug-in hybrids, are a major focus of current research and development. This book explores the future of transportation. It is divided into four sections: “Electric Vehicles Infrastructures,” “Architectures of the Electric Vehicles,” “Technologies of the Electric Vehicles,” and “Propulsion Systems.” The chapter authors share their research experience regarding the main barriers in electric vehicle implementation, their thoughts on electric vehicle modelling and control, and network communication challenges

Roadway-Embedded Transmitters and Multi-Pad Receivers for High Power Dynamic Wireless Power Transfer

Electric vehicles (EVs) offer considerable economic and environmental benefits to society. Despite the decreasing vehicle costs and increasing range of newer EVs, the problem of range anxiety still exists. Range anxiety, at its core, is an issue of charging speeds rather than a concern about the driving range. Dynamic wireless charging of EVs is seen as a potential solution to this issue of range anxiety. Further, wireless charging technology also helps the push towards level 5 autonomy and opens new opportunities for how an EV can be utilized. Dynamic wireless power transfer (DWPT) systems typically require a high initial investment due to the scale of deployment needed and require a certain level of EV adoption before they become economically viable. The challenges facing DWPT technologies are broadly categorized into development, deployment and operation challenges. To address the deployment challenges, this dissertation presents the pavement integration of DWPT systems, and the design and validation of concrete-embedded wireless charging pads. To improve infrastructure utilization and address the operation challenge, different vehicle classes need to recharge from the same charging infrastructure. This is made possible by the use of multi-pad receivers, which allow different vehicle classes to receive different power levels using the same charging infrastructure. This work presents a scaled-down version of a multi-pad receiver system to demonstrate the operation and scalability of these modular receivers. To help further reduce the cost of development and implementation of DWPT systems, finite element method (FEM) and circuit simulation models are presented. The time-domain simulations can be used to develop and validate various control and communication schemes without the need for expensive hardware implementation. Finally, leakage magnetic field reduction to ensure safety and compliance for DWPT systems is discussed, and an example system is analyzed using FEM simulations

Electric Vehicle Efficient Power and Propulsion Systems

Vehicle electrification has been identified as one of the main technology trends in this second decade of the 21st century. Nearly 10% of global car sales in 2021 were electric, and this figure would be 50% by 2030 to reduce the oil import dependency and transport emissions in line with countries’ climate goals. This book addresses the efficient power and propulsion systems which cover essential topics for research and development on EVs, HEVs and fuel cell electric vehicles (FCEV), including: Energy storage systems (battery, fuel cell, supercapacitors, and their hybrid systems); Power electronics devices and converters; Electric machine drive control, optimization, and design; Energy system advanced management methods Primarily intended for professionals and advanced students who are working on EV/HEV/FCEV power and propulsion systems, this edited book surveys state of the art novel control/optimization techniques for different components, as well as for vehicle as a whole system. New readers may also find valuable information on the structure and methodologies in such an interdisciplinary field. Contributed by experienced authors from different research laboratory around the world, these 11 chapters provide balanced materials from theorical background to methodologies and practical implementation to deal with various issues of this challenging technology. This reprint encourages researchers working in this field to stay actualized on the latest developments on electric vehicle efficient power and propulsion systems, for road and rail, both manned and unmanned vehicles

Energy management in electric vehicles: Development and validation of an optimal driving strategy

Electric vehicles (EVs) are a promising alternative energy mode of transportation for the future. However, due to the limited range and relatively long charging time, it is important to use the stored battery energy in the most optimal manner possible. Existing research has focused on improvements to the hardware or improvements to the energy management strategy (EMS). However, EV drivers may adopt a driving strategy that causes the EMS to operate the EV hardware in inefficient regimes just to fulfil the driver demand. The present study develops an optimal driving strategy to help an EV driver choose a driving strategy that uses the stored battery energy in the most optimal manner. First, a strategy to inform the driver about his/her current driving situation is developed. Then, two separate multi-objective strategies, one to choose an optimal trip speed and another to choose an optimal acceleration strategy, are presented. Finally, validation of the optimal driving strategy is presented for a fleet-style electric bus. The results indicated that adopting the proposed approach could reduce the electric bus’ energy consumption from about 1 kWh/mile to 0.6-0.7 kWh/mile. Optimization results for a fixed route around the Missouri S&T campus indicated that the energy consumption of the electric bus could be reduced by about 5.6% for a 13.9% increase in the trip time. The main advantage of the proposed strategy is that it reduces the energy consumption while minimally increasing the trip time. Other advantages are that it allows the driver flexibility in choosing trip parameters and it is fairly easy to implement without significant changes to existing EV designs. --Abstract, page iii