Energy storage and control optimization for an electric vehicle

Two big issues involving electric vehicles are energy supply and power management control. To deal with the energy supply problem, this paper proposes the application of a hybrid energy source system, composed of battery pack and ultracapacitor bank. The power management control between the energy supplies was defined by a fuzzy logic with inference rules optimized through genetic algorithm. The genetic algorithm optimizes lower and upper limits of membership functions aiming to reduce the hybrid energy source system total mass while maximizing the electric vehicle drive range and performance. Through the Pareto frontier, we found the best trade‐off solution.     

A comprehensive review on energy management strategies of hybrid energy storage system for electric vehicles

The attention on green and clean technology innovations is highly demanded of a modern era. Transportation has seen a high rate of growth in today's cities. The conventional internal combustion engine‐operated vehicle liberates gasses like carbon dioxide, carbon monoxide, nitrogen oxides, hydrocarbons, and water, which result in the increased surface temperature of the earth. One of the optimum solutions to overcome fossil fuel degrading and global warming is electric vehicle. The challenging aspect in electric vehicle is its energy storage system. Many of the researchers mainly concentrate on the field of storage device cost reduction, its age increment, and energy densities' improvement. This paper explores an overview of an electric propulsion system composed of energy storage devices, power electronic converters, and electronic control unit. The battery with high‐energy density and ultracapacitor with high‐power density combination paves a way to overcome the challenges in energy storage system. This study aims at highlighting the various hybrid energy storage system configurations such as parallel passive, active, battery–UC, and UC–battery topologies. Finally, energy management control strategies, which are categorized in global optimization, are reviewed. Copyright © 2017 John Wiley & Sons, Ltd.     

An energy matching method for battery electric vehicle and hydrogen fuel cell vehicle based on source energy consumption rate

The smart cities development requires reducing energy consumption and using as much renewable energy as possible, so the widespread use of new energy vehicles is a very important measure. In this work, for the energy system configuration and energy efficiency balance of new energy vehicles, we propose an energy matching method to study its energy efficiency from the view point for energy life cycle. Nowadays, new energy vehicles mainly include battery electric vehicles (BEV) and hydrogen fuel cell vehicles (HFCEV). Firstly, we proposed the Source to Range (STR) model. Then, based on STR model, we used energy efficiency analysis chart to visually represent the conversion, delivery and consumption of the vehicle energy life cycle. Furthermore, we proposed a Source Energy Consumption Rate (SECR), which is used to evaluate the vehicles energy efficiency. Finally, based on STR model, we obtained the dividing line of the same SECR for new energy vehicles and equivalent fuel vehicles, which provides constraints on the vehicle energy system design. The results show that STR model can provide an effective tool for energy matching and energy efficiency analysis of new energy vehicles, and has a reference for product development of new energy vehicles.     

电动汽车的能耗效率分析及提高能耗经济性的研究

通过对比电动汽车和内燃机汽油车的热效率及能耗,得出电动汽车的热效率及能耗明显优于内燃机汽油车的结论,并推断出降低电动汽车的运行能耗、提高其经济性是推动电动汽车产业化的关键因素之一。从整车动力系统、电池以及充电设备等几个方面分析了提高电动汽车能耗经济的途径,指出了今后需要重点研究的关键性问题。     

An analysis for the need of a battery energy storage system in tracking wind power schedule output

电池储能系统(battery energy storage system,BESS)在风储联合应用中具有多种功能,利用电池储能系统提高风电并网调度运行能力是当前研究的热点之一.文章基于我国北方某风电场历史运行数据与预测数据,依据预测误差评价指标和风电场预报考核指标的综合评价方法对风电场预测数据进行分析研究,归纳了预测误差的概率分布特征;提出利用电池储能系统提高风电跟踪计划出力能力,统计并量化出电池储能系统用于跟踪计划出力场合的作用范围;通过仿真验证电池储能系统在风储联合系统中提高风电跟踪计划出力控制策略的有效性和可行性.     

Economic evaluation of fast charging electric vehicle station with second-use batteries energy storage system

由于电动汽车快速充电站大功率快速充电的特性会对电网的稳定造成冲击,因此考虑在电动车快速充电站中配置电池储能系统（BESS）,对充电站负荷进行削峰填谷,从而减少充电站变压器配置容量、缓解大功率快速充电对电网的不利影响。考虑到目前我国大量退役动力电池亟待回收利用的现状,结合梯次利用电池储能系统,建立了基于电动汽车快速充电站整体成本与收益的经济性评估模型,以快速充电站年净收益最大为目标函数,采用改进的遗传算法对模型优化求解。结合算例对快速充电站不配置储能、配置常规电池储能和配置梯次电池储能等不同情况进行了经济性评估,并综合考虑经济性与储能削减负荷的效果,确定了梯次电池储能系统最优容量配置方案。     

Neural network-based energy management of multi-source (battery/UC/FC) powered electric vehicle

Due to increased environmental pollution and global warming concerns, the use of energy storage units that can be supported by renewable energy resources in transportation becomes more of an issue and plays a vital role in terms of clean energy solutions. However, utilization of multiple energy storage units together in an electric vehicle makes the powertrain system more complex and difficult to control. For this reason, the present study proposes an advanced energy management strategy (EMS) for range extended battery electric vehicles (BEVs) with complex powertrain structure. Hybrid energy storage system (HESS) consists of battery, ultra-capacitor (UC), fuel cell (FC) and the vehicle is propelled with two complementary propulsion machines. To increase powertrain efficiency, traction power is simultaneously shared at different rates by propulsion machines. Propulsion powers are shared by HESS units according to following objectives: extending battery lifetime, utilizing UC and FC effectively. Primarily, to optimize the power split in HESS, a convex optimization problem is formulated to meet given objectives that results 5 years prolonged battery lifetime. However, convex optimization of complex systems can be arduous due to the excessive number of parameters that has to be taken into consideration and not all systems are suitable for linearization. Therefore, a neural network (NN)-based machine learning (ML) algorithm is proposed to solve multi-objective energy management problem. Proposed NN model is trained with convex optimization outputs and according to the simulation results the trained NN model solves the optimization problem within 92.5% of the convex optimization one.     

A fast classification method of retired electric vehicle battery modules and their energy storage application in photovoltaic generation

The fading characteristics of 60 Ah decommissioned electric vehicle battery modules were assessed employing capacity calibration, electrochemical impedance spectroscopy, and voltage measurement of parallel bricks inside modules. The correlation between capacity and internal resistance or voltage was analyzed. Then, 10 consistent retired modules were packed and configured in a photovoltaic (PV) power station to verify the practicability of their photovoltaic energy storage application. The results show that the capacity attenuation of most retired modules is not severe in a pack while minor modules with state of health (SOH) less than 80% bring about the retirement of the whole pack as a result of the buckets effect. There is no obvious correlation between capacities of retired battery modules and their lithium-ion diffusion coefficients or charge transfer resistance or ohmic resistance, whose reliability is low as the consistency indexes of decommissioning battery modules. The maximum off load voltage difference ΔU_max at low state of charge (SOC) values has a good negative linear correlation with the capacity of retired modules, suggesting that the ΔU_max value at low SOC values can be considered as a characteristic index for fast classification of retired battery modules for large-scale second-life application. A PV power station equipped with retired battery energy storage system (RBESS) can maximize the photovoltaic self-utilization rate. It is an important way to reutilization of retired battery that RBESSs are configured with distributed PV power stations.     

Research on optimal confguration of hybrid energy storage capacity for wind-solar generation system

储能系统可以有效解决微电网中分布式可再生能源特别是风光互补发电的间歇性、波动性以及“源”与“荷”错位的问题。不同储能技术在响应时间、容量规模、技术成熟度及成本等方面各有特点,两种或多种储能技术耦合将可以更有效地满足用电系统的技术性和经济性的要求。针对电力用户对分布式可再生能源的利用情况,本文提出一种由压缩空气储能、锂电池和超级电容器组成的混合储能系统,建立了三种储能的数学模型,针对其不同的特性,提出了基于二次移动平均滤波的储能系统功率分配方法和基于连续性运行的容量优化配置方法。基于某个实际的用户负荷进行了案例分析,得到了混合储能系统的功率和容量配置结果,并分析了其运行特性。研究表明,在分布式可再生能源微电网中,多种储能技术耦合既能充分发挥每种储能的优势,又可以通过相互配合弥补各自的劣势,这对于可再生能源的充分利用和满足用电负荷的严苛需求具有重要的作用和意义,在分布式能源利用领域具有较好的工程应用前景。     

Energy management strategy and capacity optimization for CCHP system integrated with electric-thermal hybrid energy storage system

In order to improve the comprehensive energy utilization rate of combined cooling, heating, and power (CCHP) system, a hybrid energy storage system (HESS) is proposed in this paper consisting of electric and thermal energy storage systems. And the overall optimization design and operation of CCHP system with HESS are the main problems to be solved in application. Therefore, the topology and the energy flow model of CCHP system with HESS are established and analyzed according to the energy conversion characteristics of the component equipment. Moreover, combined with five evaluative restrictions for HESS system, a rule-based energy management strategy is designed to realize the decoupling regulation of electric energy and thermal energy in CCHP system. On this basis, a multi-objective optimization model is studied by taking the indicators of annual cost ratio, the primary energy consumption ratio, and loss energy ratio, and then the capacity parameters are optimized by particle swarm optimization algorithm (PSOA). Finally, a case is carried out to compare the energy allocation situations and capacity optimization results between CCHP system with HESS and CCHP system with single thermal energy storage system (ST). Results show that the capacity of ICE is reduced by 34%, and the annual cost and the primary energy consumption are saved about 7.69% and 18.47%, respectively, demonstrating that HESS has better optimization effect and applicable for small-scale CCHP system.     

Analytical method to evaluate fuel consumption of hybrid electric vehicles at balanced energy content of the electric storage devices

Innovative analytically based method to calculate corrected fuel consumption of parallel and series hybrid electric vehicles (HEVs) at balanced energy content of the electric storage devices is proposed and validated in the paper. The proposed analytical method is generally applicable and features highly accurate corrected fuel consumption results. It enables calculation of the corrected fuel consumption out of a single fuel consumption test run in a single analytic post-processing step. An additional fuel consumption test run might be needed to obtain highly accurate results if ratio of the energy content deviation of the electric storage devices to the energy used for vehicle propulsion over the test cycle is high. Proposed method enables consideration of non-linear energy flow changes and non-linear HEV component efficiency changes caused by the energy management strategy or by the component characteristics. The method therefore features highly accurate results out of the minimum number of fuel consumption test runs and thus optimizes workload for development or optimization of HEVs. The input data of the method are characteristic energy flows and efficiencies that are derived from the energy flows on selected energy paths of HEVs.     

The ability of battery second use strategies to impact plug-in electric vehicle prices and serve utility energy storage applications

The high cost of lithium ion batteries is a major impediment to the increased market share of plug-in hybrid electric vehicles (PHEVs) and full electric vehicles (EVs). The reuse of PHEV/EV propulsion batteries in second use applications following the end of their automotive service life may have the potential to offset the high initial cost of these batteries today. Accurately assessing the value of such a strategy is exceedingly complex and entails many uncertainties. This paper takes a first step toward such an assessment by estimating the impact of battery second use on the initial cost of PHEV/EV batteries to automotive consumers and exploring the potential for grid-based energy storage applications to serve as a market for used PHEV/EV batteries. It is found that although battery second use is not expected to significantly affect today's PHEV/EV prices, it has the potential to become a common component of future automotive battery life cycles and potentially to transform markets in need of cost-effective energy storage. Based on these findings, the authors advise further investigation focused on forecasting long-term battery degradation and analyzing second-use applications in more detail.     

Long-term optimization based on PSO of a grid-connected renewable energy/battery/hydrogen hybrid system

This paper presents and evaluates three energy management systems (EMSs) based on Particle Swarm Optimization (PSO) for long-term operation optimization of a grid-connected hybrid system. It is composed of wind turbine (WT) and photovoltaic (PV) panels as primary energy sources, and hydrogen system (fuel cell –FC–, electrolyzer and hydrogen storage tank) and battery as energy storage system (ESS). The EMSs are responsible for making the hybrid system produce the demanded power, deciding on the energy dispatch among the ESS devices. The first PSO-based EMS tries to minimize the ESS utilization costs, the second one to maximize the ESS efficiency, and the third one to optimize the lifetime of the ESS devices. Long-term simulations of 25 years (expected lifetime of the hybrid system) are shown in order to demonstrate the right performance of the three EMSs and their differences. The simulations show that: 1) each EMS outperforms the others in the designed target; and 2) the third EMS is considered the best EMS, because it needs the least ESS devices, and presents the lowest total acquisition cost of hybrid system, whereas the rest of parameters are similar to the best values obtained by the other EMSs.     

Decoupling optimization of integrated energy system based on energy quality character

Connections among multi-energy systems become increasingly closer with the extensive application of various energy equipment such as gas-fired power plants and electricity-driven gas compressor. Therefore, the integrated energy system has attracted much attention. This paper establishes a gas-electricity joint operation model, proposes a system evaluation index based on the energy quality character after considering the grade difference of the energy loss of the subsystem, and finds an optimal scheduling method for integrated energy systems. Besides, according to the typical load characteristics of commercial and residential users, the optimal scheduling analysis is applied to the integrated energy system composed of an IEEE 39 nodes power system and a 10 nodes natural gas system. The results prove the feasibility and effectiveness of the proposed method.     

Application and development trends of energy storage technology in the field of traffic

纵观当前全球电力系统发展规划,智能电网,可再生能源和分布式发电,微电网以及电动汽车都列入了各国电力系统发展的重点方向,而储能技术正是实现上述领域发展必不可少的技术支撑.目前,储能技术较高的成本阻碍了其在电力系统中的应用.若将电动汽车动力电池作为电力系统的储能元件,便可使其作为传统交通工具的同时,充当电力系统的一种潜在的备用电源.通过电动汽车V2G模式和动力电池的梯次使用,将帮助电网调峰调频,促进电动汽车动力电池的产业化和多种应用,降低电动汽车的生产和使用成本,最终实现交通能源消费的电力化.本文在对电动汽车储能相关技术,基础设施建设及与之匹配的商业模式进行梳理和分析的基础上,展望电动汽车储能的发展潜力并提出相应的政策建议.     

Impact of electric vehicles on a future renewable energy‐based power system in Europe with a focus on Germany

Electric mobility is expected to play a key role in the decarbonisation of the energy system. Continued development of battery electric vehicles is fundamental to achieving major reductions in the consumption of fossil fuels and of CO₂ emissions in the transport sector. Hydrogen can become an important complementary synthetic fuel providing electric vehicles with longer ranges. However, the environmental benefit of electric vehicles is significant only if their additional electricity consumption is covered by power production from renewable energy sources. Analysing the implications of different scenarios of electric vehicles and renewable power generation considering their spatial and temporal characteristics, we investigate possible effects of electric mobility on the future power system in Germany and Europe. The time horizon of the scenario study is 2050. The approach is based on power system modelling that includes interchange of electricity between European regions, which allows assessing long‐term structural effects in energy systems with over 80% of renewable power generation. The study exhibits strong potential of controlled charging and flexible hydrogen production infrastructure to avoid peak demand increases and to reduce the curtailment of renewable power resulting in reduced system operation, generation, and network expansion costs. A charging strategy that is optimised from a systems perspective avoids in our scenarios 3.5 to 4.5 GW of the residual peak load in Germany and leads to efficiency gains of 10% of the electricity demand of plug‐in electric vehicles compared with uncontrolled loading.     

电储能修井机的研制与应用

针对修井设备电动化更新需求以及普通电动修井机推广应用受限的问题，研制了电储能修井机。该修井机以磷酸铁锂型电池作为储能装置，通过技术研发突破网电储能协同控制、电池管理及油气环境下的使用安全和现场检测评价等技术难题，形成了网电储能联合供电的电控技术、“智慧报警”防护体系的电池管理系统，实现了电池储能技术在修井机上的良好应用。经现场测试，电储能修井机可满足不同井况的修井作业需求。在停电情况下，该储能装置可独立供电作业，适用范围大，应用前景广阔。     

Integrated control strategy of vehicle supercapacitor energy storage system based on MMC

针对单辆城轨列车在起动、制动过程中对牵引网电压造成冲击从而引起网压不稳定的问题,提出一种基于MMC的车载超级电容储能系统（车载MMC-SCESS）,该系统以MMC拓扑结构作为主电路,通过将超级电容储能单元分散接入MMC子模块中,提高系统的控制灵活性与容错性;其次以车载MMC-SCESS的整体结构为研究对象,详细分析其a相桥臂电路工作原理,总结出每个储能子模块的一般工作模式。针对该储能系统主电路结构,提出采用综合控制策略,通过控制超级电容储能单元的充放电状态来实现能量在城轨列车、直流牵引网、超级电容储能系统三者之间流动。最后在Matlab/Simulink中搭建三相五电平车载MMC-SCESS仿真模型,仿真波形验证了储能系统控制策略的可行性。     

Numerical analysis of an energy storage system based on a metal hydride hydrogen tank and a lithium-ion battery pack for a plug-in fuel cell electric scooter

This work investigates on the performance of a hybrid energy storage system made of a metal hydride tank for hydrogen storage and a lithium-ion battery pack, specifically conceived to replace the conventional battery pack in a plug-in fuel cell electric scooter. The concept behind this solution is to take advantage of the endothermic hydrogen desorption in metal hydrides to provide cooling to the battery pack during operation.The analysis is conducted numerically by means of a finite element model developed in order to assess the thermal management capabilities of the proposed solution under realistic operating conditions.The results show that the hybrid energy storage system is effectively capable of passively controlling the temperature of the battery pack, while enhancing at the same time the on-board storage energy density. The maximum temperature rise experienced by the battery pack is around 12 °C when the thermal management is provided by the hydrogen desorption in metal hydrides, against a value above 30 °C obtained for the same case without thermal management. Moreover, the hybrid energy storage system provides the 16% of the total mass of hydrogen requested by the fuel cell stack during operation, which corresponds to a significant enhancement of the hydrogen storage capability on-board of the vehicle.     

An updated review of energy storage systems: Classification and applications in distributed generation power systems incorporating renewable energy resources

The demand of electric energy is increasing globally, and the fact remains that the major share of this energy is still being produced from the traditional generation technologies. However, the recent trends, for obvious reasons of environmental concerns, are indicating a paradigm shift towards distributed generation (DG) incorporating renewable energy resources (RERs). But there are associated challenges with high penetration of RERs as these resources are unpredictable and stochastic in nature, and as a result, it becomes difficult to provide immediate response to demand variations. This is where energy storage systems (ESSs) come to the rescue, and they not only can compensate the stochastic nature and sudden deficiencies of RERs but can also enhance the grid stability, reliability, and efficiency by providing services in power quality, bridging power, and energy management. This paper provides an extensive review of different ESSs, which have been in use and also the ones that are currently in developing stage, describing their working principles and giving a comparative analysis of important features and technical as well as economic characteristics. The wide range of storage technologies, with each ESS being different in terms of the scale of power, response time, energy/power density, discharge duration, and cost coupled with the complex characteristics matrices, makes it difficult to select a particular ESS for a specific application. The comparative analysis presented in this paper helps in this regard and provides a clear picture of the suitability of ESSs for different power system applications, categorized appropriately. The paper also brings out the associated challenges and suggests the future research directions.