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 review of large‐scale electrical energy storage

This paper gives a broad overview of a plethora of energy storage technologies available on the large‐scale complimented with their capabilities conducted by a thorough literature survey. According to the capability graphs generated, thermal energy storage, flow batteries, lithium ion, sodium sulphur, compressed air energy storage, and pumped hydro storage are suitable for large‐scale storage in the order of 10's to 100's of MWh; metal air batteries have a high theoretical energy density equivalent to that of gasoline along with being cost efficient; compressed air energy storage has the lowest capital energy cost in comparison to other energy storage technologies; flywheels, super conducting magnetic storage, super capacitors, capacitors, and pumped hydro storage have very low energy density; compressed air energy storage, cryogenic energy storage, thermal energy storage, and batteries have relatively high energy density; high efficiencyin tandem with high energy density results in a cost efficient storage system; and power density pitted against energy density provides a clear demarcation between power and energy applications. This paper also provides a mathematical model for thermal energy storage as a battery. Furthermore, a comprehensive techno‐economic evaluation of the various energy storage technologies would assist in the development of an energy storage technology roadmap. Copyright © 2015 John Wiley & Sons, Ltd.     

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。     

An improved particle swarm optimisation for unit commitment in microgrids with battery energy storage systems considering battery degradation and uncertainties

Using electric storage systems (ESSs) is known as a viable strategy to mitigate the volatility and intermittency of renewable distributed generators (DGs) in microgrids (MGs). Among different electric storage technologies, battery energy storage (BES) is considered as the best option. In unit commitment (UC) module, the set of committed dispatchable DGs along with their power, power exported to/imported from macrogrid and status and power of ESS units are determined. In this paper, BES degradation is considered in UC formulation and an efficient particle swarm optimisation with quadratic transfer function is proposed for solving UC in BES‐integrated MGs, while the uncertainties of demand, renewable generation and market price are considered and dealt with robust optimisation. UC is formulated as a multi‐objective optimisation problem whose objectives are MG operation cost and BES degradation. The resultant multi‐objective optimisation problem is converted into a single‐objective optimisation problem and the effect of weight factors on MG operation cost and BES lifecycle are investigated. The results show that by consideration of BES degradation in objective function, BES lifecycle increases from 350 to 500 and the minimum depth of charge increases from 5.5% to 34%; however, MG operation cost increases from $8717 to $8910.2. The results also show that by consideration of uncertainties, MG's operation cost increases by 8.22%.     

Optimal energy management strategy of fuel-cell battery hybrid electric mining truck to achieve minimum lifecycle operation costs

Proton exchange membrane fuel cell (PEMFC) electric vehicle is an effective solution for improving fuel efficiency and onboard emissions, taking advantage of the high energy density and short refuelling time. However, the higher cost and short life of the PEMFC system and battery in an electric vehicle prohibit the fuel cell electric vehicle (FCEV) from becoming the mainstream transportation solution. The fuel efficiency-oriented energy management strategy (EMS) cannot guarantee the improvement of total operating costs. This paper proposes an EMS to minimize the overall operation costs of FCEVs, including the cost of hydrogen fuel, as well as the cost associated with the degradations of the PEMFC system and battery energy storage system (ESS). Based on the PEMFC and battery performance degradation models, their remaining useful life (RUL) models are introduced. The control parameters of the EMS are then optimized using a meta-model based global optimization algorithm. This study presents a new optimal control method for a large mining truck operating on a real closed-road operation cycle, using the combined energy efficiency and performance degradation cost measures of the PEMFC system and lithium-ion battery ESS. Simulation results showed that the proposed EMS could improve the total operating costs and the life of the FCEV.     

Research progress of carbon-based lithium ion capacitor

新能源体系的建设和电子设备的飞速发展对储能器件提出了更高的要求,即要求其同时兼具较高的能量密度和功率密度。锂离子电容器（LIC）是一种基于锂离子电池（LIB）和超级电容器（EDLC）双重储能机制的储能器件,兼具超级电容器良好的功率特性和锂离子电池较高的能量密度,有望应用于混合动力汽车、轨道交通、智能电网、能源工程等领域。从锂离子电容器未来的产业化角度出发,炭材料因为资源丰富、制备简单和廉价易得是锂离子电容器的首选材料。本文综述了活性炭等正极炭材料、石墨等负极炭材料、电解液以及锂离子电容器工艺方面的研究进展,并对锂离子电容器未来的发展方向和发展前景作出了展望。     

Grid to wheel energy efficiency analysis of battery‐ and fuel cell–powered vehicles

Sustainable energy consumption is an important part of the renewable energy economy as renewable energy generation and storage. Almost one‐third of the global energy consumption can be credited to the transportation of goods and people around the globe. To move towards a renewable energy–based economy, we must adopt to a more sustainable energy consumption pattern worldwide especially in the transportation sector. In this article, a comparison is being made between the energy efficiency of a fuel cell vehicle and a battery electric vehicle. A very simple yet logical approach has been followed to determine the overall energy required by each vehicle. Other factors that hinder the progress of fuel cell vehicle in market are also discussed. Additionally, the prospects of a hydrogen economy are also discussed in detail. The arguments raised in this article are based on physics, economic analyses, and laws of thermodynamics. It clearly shows that an “electric economy” makes far greater sense than a “hydrogen economy.” The main objective of this analysis is to determine the energy efficacy of battery‐powered vehicles as compared to fuel cell–powered vehicles.     

Jaya algorithm-based energy management system for battery- and ultracapacitor-powered ultralight electric vehicle

To improve the driving performance of the electric vehicles, batteries or ultracapacitors (UCs) are frequently preferred in the energizing systems. In hybrid structures with multiple supply sources, an energy management system (EMS) is needed to improve the system efficiency, and to provide the optimum power sharing between a battery and a UC. The purpose of this study is to investigate the effectiveness of the Jaya optimization method for the urban use of the EMS of an ultralight electric vehicle powered by battery/UC. The performance of the proposed method is compared with dynamic programming (DP) that is one of the global optimization methods and particle swarm optimization (PSO) that is one of the other heuristic methods for real-time applications. The simulation results show that Jaya-EMS approached 3.1% to the DP, which yields the optimum result with respect to the total energy loss. In addition, the proposed method yields a loss of less than 1.9% from the PSO-EMS. If all the above situations are considered, the proposed EMS method has less lossy alternative solution for the real-time applications.     

A hierarchical management system for energy storage batteries

现有的储能电池管理系统大都是从电动汽车电池管理系统直接引用过来的,其管理的电池容量小,功能单一,实时性较差.兆瓦级储能系统由大容量电池串联,对电池系统管理效率提出了新要求.为解决这一问题,提出了一种3层分层式储能电池管理系统.对底层BMU,中层BCMS和顶层BAMS从硬件和软件设计两方面做了详细地介绍.分层式储能电池管理系统具有检测与计算,电池单体均衡管理,高压管理,统计存储,充放电管理,报警功能和通信.     

Variable structure battery-based fuel cell hybrid power system and its incremental fuzzy logic energy management strategy

A hybrid power system consists of a fuel cell and an energy storage device like a battery and/or a supercapacitor possessing high energy and power density that beneficially drives electric vehicle motor. The structures of the fuel cell-based power system are complicated and costly, and in energy management strategies (EMSs), the fuel cell's characteristics are usually neglected. In this study, a variable structure battery (VSB) scheme is proposed to enhance the hybrid power system, and an incremental fuzzy logic method is developed by considering the efficiency and power change rate of fuel cell to balance the power system load. The principle of VSB is firstly introduced and validated by discharge and charge experiments. Subsequently, parameters matching of the fuel cell hybrid power system according to the proposed VSB are designed and modeled. To protect the fuel cell as well as ensure the efficiency, a fuzzy logic EMS is formulated via setting the fuel cell operating in a high efficiency and generating an incremental power output within the affordable power slope. The comparison between a traditional deterministic rules-based EMS and the designed fuzzy logic was implemented by numerical simulation in three different operation conditions: NEDC, UDDS, and user-defined driving cycle. The results indicated that the incremental fuzzy logic EMS smoothed the fuel cell power and kept the high efficiency. The proposed VSB and incremental fuzzy logic EMS may have a potential application in fuel cell vehicles.     

Improvement of ultracapacitors-energy usage in fuel cell based hybrid electric vehicle

Hybrid electric power systems based on fuel cell stack and energy storage sources like batteries and ultracapacitors are a plausible solution to vehicle electrification due to their balance between acceleration performance and range. Having a high degree of hybridization can be advantageous, considering the different characteristics of the power sources. Some parameters to be considered are: specific power and energy, energy and power density, lifetime, cost among others. Ultracapacitors (UC) are of particular interest in electric vehicle applications due to its high-power capability, which is commonly required during acceleration. UCs are commonly used without a power electronics interface due to the high-power processing requirement. Although connecting UCs directly to the DC bus, without using a power converter, presents considerable advantages, the main disadvantage is related to the UC energy-usage capability, which is limited by constant DC bus control. This paper proposes a novel energy-management strategy based on a fuzzy inference system, for fuel-cell/battery/ultracapacitor hybrid electric vehicles. The proposed strategy is able to control the charge and discharge of the UC bank in order to take advantage of its energy storage capability. Experimental results show that the proposed strategy reduces the waste of energy due to dynamic brake in 14%. This represents a reduction in energy consumption from 218 Wh/km to 192 Wh/km for the same driving conditions. By using the proposed energy management strategy, the estimated fuel efficiency in miles per gallon equivalent was also increase from 96 mpge to 109 mpge.     

Electric vehicle energy consumption modelling and estimation—A case study

Electric vehicles (EVs) have a limited driving range compared to conventional vehicles. Accurate estimation of EV's range is therefore a significant need to eliminate “range anxiety” that refers to drivers' fear of running out of energy while driving. However, the range estimators used in the currently available EVs are not sufficiently accurate. To overcome this issue, more accurate range estimation techniques are investigated. Nonetheless, an accurate power‐based EV energy consumption model is crucial to obtain a precise range estimation. This paper describes a study on EV energy consumption modelling. For this purpose, EV modelling is carried out using MATLAB/Simulink software based on a real EV in the market, the BMW i3. The EV model includes vehicle powertrain system and longitudinal vehicle dynamics. The powertrain is modelled using efficiency maps of the electric motor and the power electronics' data available for BMW i3. It also includes a transmission and a battery model (ie, Thevenin equivalent circuit model). A driver model is developed as well to control the vehicle's speed and to represent human driver's behaviour. In addition, a regenerative braking strategy, based on a series brake system, is developed to model the behaviour of a real braking controller. Auxiliary devices are also included in the EV model to improve energy consumption estimation accuracy as they can have a significant impact on that. The vehicle model is validated against published energy consumption values that demonstrates a satisfactory level of accuracy with 2% to 6% error between simulation and experimental results for Environmental Protection Agency and NEDC tests.     

Design and investigation on portable energy storage device based on sodium-ion batteries

报道了一种新型移动式钠离子电池储能系统,其核心储能器件为钠离子电池,采用自制的NaNi_1/3Fe_1/3Mn_1/3O₂为正极材料,负极材料为硬碳。采用XRD、DSC等对正极材料的结构和热稳定性进行分析表征。设计制作了1 A·h软包型钠离子电池,对其电化学性能与安全性进行测试。在此基础上设计了钠离子电池包以及基于钠离子电池的0.1 kW·h新型移动式储能系统。该系统在家用储能、军事电源、低速电动车上有良好的应用前景。     

Distributed generation integrated with thermal unit commitment considering demand response for energy storage optimization of smart grid

This paper deals with an optimal battery energy storage capacity for the smart grid operation. Distributed renewable generator and conventional thermal generator are considered as the power generation sources for the smart grid. Usually, a battery energy storage system (BESS) is used to satisfy the transmission constraints but installation cost of battery energy storage is very high. Sometimes, it is not possible to install a large capacity of the BESS. On the other hand, the competition of the electricity market has been increased due to the deregulation and liberalization of the power market. Therefore, the power companies are required to reduce the generation cost in order to maximize the profit. In this paper, a thermal units commitment program considers the demand response system to satisfy the transmission constraints. The BESS capacity can be reduced by the demand response system. The electric vehicle (EV) and heat pump (HP) in the smart house are considered as the controllable loads of the demand side. The effectiveness of the proposed method is validated by extensive simulation results which ensure the reduction of BESS capacity and power generation cost, and satisfy the transmission constraints.     

Application and prospect of zinc nickel battery in energy storage technology

本文介绍了近几年电力储能在全球储能领域的现况及电力储能在现有储能系统中的应用规模。针对目前较成熟的电化学储能电池进行了分析,着重分析了锌镍电池的特点,首先对锌镍电池的低温放电性能、寿命、大电流充放等性能进行了阐述,模拟储能系统充放电实验的结果表明锌镍电池具有循环寿命长和充放电效率高等特点。其次对单液流锌镍电池的工作原理进行了介绍,就目前单液流锌镍电池的各个型号的中试产品以及50 kW·h储能系统进行了总结和讨论,分析表明锌镍电池作为一种新型的蓄电池,其循环寿命长、安全性能好、制造和维护成本较低,随着近几年新材料的发展,锰正极的锌基电池实验成功,促进了锌空气电池、锌铁电池等系列锌基电池的研发,锌镍电池未来在储能市场将会大放异彩。     

The application of Supercapacitor energy storage technology in the alongside replenishment equipment

本工作分析了航行横向补给系统的电动机再生发电问题,通过对蓄电池储能、超导线圈储能、飞轮储能和超级电容储能技术特点的对比,选用超级电容储能系统回收和利用再生电能,提出了超级电容储能系统的设计和应用方案,并对基本设计参数进行了计算。航行横向补给过程中,受到补给船和接收船距离不断变化的影响,补给装置绞车电机在电动和发电两种状态间频繁交互运行。电动机在发电状态下向变频器直流母线反馈大量再生电能,影响电网质量和设备的正常工作。由于超级电容具有功率密度高、充放电功率大、使用寿命长和工作温度范围广的优点,非常适用于电能的快速回收和释放,能够降低系统功率、减小对电网的影响、节约能源,在需要反复进行电能回收和释放的设备中具有较好的应用前景。     

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。     

Performance of an environmentally benign acid base flow battery at high energy density

An increasing fraction of energy is generated by intermittent sources such as wind and sun. A straightforward solution to keep the electricity grid reliable is the connection of large‐scale electricity storage to this grid. Current battery storage technologies, while providing promising energy and power densities, suffer from a large environmental footprint, safety issues, and technological challenges. In this paper, the acid base flow battery is re‐established as an environmental friendly means of storing electricity using electrolyte consisting of NaCl salt. To achieve a high specific energy, we have performed charge and discharge cycles over the entire pH range (0–14) at several current densities. We demonstrate stable performance at high energy density (2.9 Wh L^?1). Main energy dissipation occurs by unwanted proton and hydroxyl ion transport and leads to low coulombic efficiencies (13%–27%).     

Life-cycle energy efficiency estimation of large-scale ammonia fuel energy storage system

本文讨论了氨作为燃料使用会具备与传统化石燃料显著不同的环境效益,并进一步探讨了氨作为储能介质的特点,包括储能密度和规模大、受地理条件约束小、便于运输存储等。本文还针对目前的合成氨路线从理论分析和工业实际两个方面对合成效率进行了估算和评价。针对目前国内核能、风能、太阳能等清洁能源电力的低谷或弃电问题,建议采用以制氨的方式存储或外运,以便于在电力不足时将其用于发电。建议并评估了几条基于制氨并发电的路线,并基于现有氨燃料的发电效率计算了各路线在全生命周期内的总储能效率（25%～40%）和以电换电的效率[2.5～4.0(度/10度）]。     

A techno‐economic analysis on NaS battery energy storage system supporting peak shaving

The merits of electricity grid in Shanghai and sodium sulfur (NaS) storage techniques situation are introduced. High‐energy NaS battery energy storage system (BESS) is very suitable for peak shaving of electricity grid. A cost–benefit analysis model of NaS BESS is established to study the electricity price mechanism in load shift in the light of an example of NaS BESS in Meisei University. Capacity price, energy price and twofold electricity price mechanism are discussed under the fixed payback period. The results show that twofold electric power price mechanism is fitter for NaS BESS than onefold energy price mechanism while onefold capacity price mechanism is not suitable for NaS BESS. The discharge price of NaS BESS has an advantage over Shanghai's electricity price in industrial and commercial peak periods when its construction cost descends to 1000 yuan kWh^?1. Copyright © 2015 John Wiley & Sons, Ltd.