Analysis of Hybrid Rechargeable Energy Storage Systems in Series Plug-In Hybrid Electric Vehicles Based on Simulations

In this paper, an extended analysis of the performance of different hybrid Rechargeable Energy Storage Systems (RESS) for use in Plug-in Hybrid Electric Vehicle (PHEV) with a series drivetrain topology is analyzed, based on simulations with three different driving cycles. The investigated hybrid energy storage topologies are an energy optimized lithium-ion battery (HE) in combination with an Electrical Double-Layer Capacitor (EDLC) system, in combination with a power optimized lithium-ion battery (HP) system or in combination with a Lithium-ion Capacitor (LiCap) system, that act as a Peak Power System. From the simulation results it was observed that hybridization of the HE lithium-ion based energy storage system resulted from the three topologies in an increased overall energy efficiency of the RESS, in an extended all electric range of the PHEV and in a reduced average current through the HE battery. The lowest consumption during the three driving cycles was obtained for the HE-LiCap topology, where fuel savings of respectively 6.0%, 10.3% and 6.8% compared with the battery stand-alone system were achieved. The largest extension of the range was achieved for the HE-HP configuration (17% based on FTP-75 driving cycle). HP batteries however have a large internal resistance in comparison to EDLC and LiCap systems, which resulted in a reduced overall energy efficiency of the hybrid RESS. Additionally, it was observed that the HP and LiCap systems both offer significant benefits for the integration of a peak power system in the drivetrain of a Plug-in Hybrid Electric Vehicle due to their low volume and weight in comparison to that of the EDLC system.

A comprehensive review on hybrid electric vehicles: architectures and components

The rapid consumption of fossil fuel and increased environmental damage caused by it have given a strong impetus to the growth and development of fuelefficient vehicles. Hybrid electric vehicles (HEVs) have evolved from their inchoate state and are proving to be a promising solution to the serious existential problem posed to the planet earth. Not only do HEVs provide better fuel economy and lower emissions satisfying environmental legislations, but also they dampen the effect of rising fuel prices on consumers. HEVs combine the drive powers of an internal combustion engine and an electrical machine. The main components of HEVs are energy storage system, motor, bidirectional converter and maximum power point trackers (MPPT, in case of solar-powered HEVs). The performance of HEVs greatly depends on these components and its architecture. This paper presents an extensive review on essential components used in HEVs such as their architectures with advantages and disadvantages, choice of bidirectional converter to obtain high efficiency, combining ultracapacitor with battery to extend the battery life, traction motors’ role and their suitability for a particular application. Inclusion of photovoltaic cell in HEVs is a fairly new concept and has been discussed in detail. Various MPPT techniques used for solar-driven HEVs are also discussed in this paper with their suitability.

Realization and Analysis of Good Fuel Economy and Kinetic Performance of a Low-cost Hybrid Electric Vehicle

By using high-power and high-efficiency propulsion systems,current hybrid electric vehicles（HEVs） in market can achieve excellent fuel economy and kinetic performance.However,it is the cost of current HEVs that hinders HEVs coming into widespread use.A novel hybrid electric propulsion system is designed to balance HEV cost and performance for developing markets.A battery/supercapacitor-based hybrid energy storage system（HESS） is used to improve energy conversion efficiency and reduce battery size and cost.An all-in-one-controller（AIOC） which integrates engine electronic control unit（ECU）,motor ECU,and HESS management system is developed to save materials and energy,and reduce the influence of distribution parameters on circuit.As for the powertrain configuration,four schemes are presented：belt-driven starter generator（BSG） scheme,four-wheel drive HEV scheme,full HEV scheme,and ranger-extender electric vehicle（EV） scheme.Component selection and parameter matching for the propulsion system are performed,and an energy management strategy is developed based on powertrain configuration and selected components.Forward-facing simulation models are built,comprehending the control strategy based on the optimal engine torque for the low-cost hybrid electric propulsion system.Co-simulation of AVL CRUISE and Matlab/Simulink is presented and the best scheme is selected.The simulation results indicate that,for the best design,fuel consumption in urban driving condition is 4.11 L/（100 km） and 0-50 km/h accelerating time is 10.95 s.The proposed research can realize low-cost concept for HEV while achieving satisfactory fuel economy and kinetic performance,and help to improve commercialization of HEVs.

Towards Realistic Vibration Testing of Large Floor Batteries for Battery Electric Vehicles (BEV)

This contribution shows an analysis of vibration measurement on large floor-mounted traction batteries of Battery Electric Vehicles(BEV).The focus lies on the requirements for a realistic replication of the mechanical environments in a testing laboratory.Especially the analysis on global bending transfer functions and local corner bending coherence indicate that neither a fully stiff fixation of the battery nor a completely independent movement on the four corners yields a realistic and conservative test scenario.The contribution will further show what implication these findings have on future vibration&shock testing equipment for large traction batteries.Additionally,it will cover an outlook on how vibration behavior of highly integrated approaches(cell2car)changes the mechanical loads on the cells.

Stochastic Security-constrained Unit Commitment Considering Electric Vehicles, Energy Storage Systems, and Flexible Loads with Renewable Energy Resources

In this paper, a new formulation for modeling the problem of stochastic security-constrained unit commitment along with optimal charging and discharging of large-scale electric vehicles, energy storage systems, and flexible loads with renewable energy resources is presented. The uncertainty of renewable energy resources is considered as a scenario-based model. In this paper, a multi-objective function which considers the reduction of operation cost, no-load and startup/shutdown costs, unserved load cost, load shifting, carbon emission, optimal charging and discharging of energy storage systems, and power curtailment of renewable energy resources is considered. The proposed formulation is a mixed-integer linear programming(MILP) model, of which the optimal global solution is guaranteed by commercial solvers. To validate the proposed formulation, several cases and networks are considered for analysis, and the results demonstrate the efficiency.

The effect of electric vehicle energy storage on the transition to renewable energy

The most viable path to alleviate the Global Climate Change is the substitution of fossil fuel power plants for electricity generation with renewable energy units.This substitution requires the development of very large energy storage capacity,with the inherent thermodynamic irreversibility of the storage-recovery process.Currently,the world experiences a significant growth in the numbers of electric vehicles with large batteries.A fleet of electric vehicles is equivalent to an efficient storage capacity system to supplement the energy storage system of the electricity grid.Calculations based on the hourly demand-supply data of ERCOT,a very large electricity grid,show that a fleet of electric vehicles cannot provide all the needed capacity and the remaining capacity must be met by hydrogen.Even though the storage capacity of the batteries is close to 1–2%of the needed storage capacity of the grid,the superior round-trip storage efficiency of batteries reduces the energy dissipation associated with the storage and recovery processes by up to 38%and the total hydrogen storage capacity by up to 50%.The study also shows that anticipated improvements in the round-trip efficiencies of batteries are almost three times more effective than improvements in hydrogen storage systems.

Modeling of fast charging station equipped with energy storage

The popularization of EVs(electric vehicles) has brought an increasingly heavy burden to the development of charging facilities. To meet the demand of rapid energy supply during the driving period, it is necessary to establish a fast charging station in public area. However, EVs arrive at the charging station randomly and connect to the distribution network for fast charging, it causes the grid power to fluctuate greatly and the peak-valley loads to alternate frequently, which is harmful to the stability of distribution network. In order to reduce the power fluctuation of random charging, the energy storage is used for fast charging stations. The queuing model is determined to demonstrate the load characteristics of fast charging station, and the state space of fast charging station system is described by Markov chain. After that the power of grid and energy storage is quantified as the number of charging pile, and each type of power is configured rationally to establish the random charging model of energy storage fast charging station. Finally, the economic benefit is analyzed according to the queuing theory to verify the feasibility of the model.

Zn-air batteries for electric vehicles

The increasingly serious environmental challenges have gradually aroused people's interest in electric vehicles.Over the last decade,governments and automakers have collaborated on the manufacturing of electric vehicles with high performance.Cutting-edge battery technologies are pivotal for the performance of electric vehicles.Zn-air batteries are considered as potential power batteries for electric vehicles due to their high capacity.Zn-air battery researches can be classified into three categories:primary batteries,mechanically rechargeable batteries,and chemically rechargeable batteries.The majority of current studies aim at developing and improving chemically rechargeable and mechanically rechargeable Zn-air batteries.Researchers have tried to use catalytic materials design and device design for Zn-air batteries to make it possible for their applications in electric vehicles.This review will highlight the state-of-the-art in primary batteries,mechanically rechargeable batteries,and chemically rechargeable batteries,revealing the prospects of Zn-air batteries for electric vehicles.

Fuzzy Adaptive Filtering-Based Energy Management for Hybrid Energy Storage System

Regarding the problem of the short driving distance of pure electric vehicles,a battery,super-capacitor,and DC/DC converter are combined to form a hybrid energy storage system(HESS).A fuzzy adaptive filtering-based energy management strategy(FAFBEMS)is proposed to allocate the required power of the vehicle.Firstly,the state of charge(SOC)of the super-capacitor is limited according to the driving/braking mode of the vehicle to ensure that it is in a suitable working state,and fuzzy rules are designed to adaptively adjust the filtering time constant,to realize reasonable power allocation.Then,the positive and negative power are determined,and the average power of driving/braking is calculated so as to limit the power amplitude to protect the battery.To verify the proposed FAFBEMS strategy for HESS,simulations are performed under the UDDS(Urban Dynamometer Driving Schedule)driving cycle.The results show that the FAFBEMS strategy can effectively reduce the current amplitude of the battery,and the final SOC of the battery and super-capacitor is optimized to varying degrees.The energy consumption is 7.8%less than that of the rule-based energy management strategy,10.9%less than that of the fuzzy control energy management strategy,and 13.1%less than that of the filtering-based energy management strategy,which verifies the effectiveness of the FAFBEMS strategy.

Energy management strategy for a parallel hybrid electric vehicle equipped with a battery/ultra-capacitor hybrid energy storage system

To solve the low power density issue of hybrid electric vehicular batteries, a combination of batteries and ultracapacitors (UCs) could be a solution. The high power density feature of UCs can improve the performance of battery/UC hybrid energy storage systems (HESSs). This paper presents a parallel hybrid electric vehicle (HEV) equipped with an internal combus- tion engine and an HESS. An advanced energy management strategy (EMS), mainly based on fuzzy logic, is proposed to improve the fuel economy of the HEV and the endurance of the HESS. The EMS is capable of determining the ideal distribution of output power among the internal combustion engine, battery, and UC according to the propelling power or regenerative braking power of the vehicle. To validate the effectiveness of the EMS, numerical simulation and experimental validations are carried out. The results indicate that EMS can effectively control the power sources to work within their respective efficient areas. The battery load can be mitigated and prolonged battery life can be expected. The electrical energy consumption in the HESS is reduced by 3.91% compared with that in the battery only system. Fuel consumption of the HEV is reduced by 24.3% compared with that of the same class conventional vehicles under Economic Commission of Europe driving cycle.

Emission Trading Based Optimal Scheduling Strategy of Energy Hub with Energy Storage and Integrated Electric Vehicles

This paper focuses on the optimal scheduling of the district energy system with multiple energy supply modes and flexible loads.For multi-energy system(MES),the energy hub(EH)model including energy storage system and integrated electric vehicle(EV)is established.Based on the model,the influence of pollutant trading market on total operation cost is analyzed,and the optimal scheduling strategy is further put forward to realize the minimum purchase cost and emission tax cost of the MES.Finally,this paper compares the economic benefit of the fixed mode and the response mode,and discusses the contribution of the energy storage device and the multi-energy complementary mode to energy utilization efficiency.The simulation results indicate that optimal scheduling strategy of the EH can coordinate various energy complementary modes reasonably.Meanwhile,the proposed strategy is able to improve the operation economy of the EH,and ensure the better response effect of the demand side.The sensitivity analysis demonstrates the impact of pollutant emission price change on emission reduction.

A comprehensive review on energy storage in hybrid electric vehicle

The sharp inclination in the emissions from conventional vehicles contribute to a significant increase in environmental issues,besides the energy crises and low conversion efficiency leads to the evolution of electric vehicles(EV).Hybrid electric vehicles(HEV) have efficient fuel economy and reduce the overall running cost,but the ultimate goal is to shift completely to the pure electric vehicle.Despite this,the main obstruction of HEV is energy storage capability.An EV requires high specific power(W/kg) and high specific energy(W$h/kg) to increase the distance travelled and reduce the time required for charging.The main focus of this paper is on the energy sources as these are the main components in EVs towards making them eco-friendly and cost-effective.Various topologies of EV technology such as HEVs,plug-in HEVs,and many more have been discussed.These topologies of EVs are based on the diverse combination of batteries,fuel cells,super-capacitor,flywheels,regenerative braking systems,which are used as energy sources and energy storage devices.

Complementarity of electric vehicles and pumped-hydro as energy storage in small isolated energy systems:case of La Palma,Canary Islands

Isolated energy systems in archipelagos are characterized for having a great dependence on fossil sources due to isolation and territorial fragmentation.The island of La Palma is situated on the northwest of the Canary Islands,and its electric system is very small.Sustainability policies planned by local authorities are aimed to increase the share of renewable energies and the reduction of fossil energies.However,intermittence and the concentration of unmanageable renewable energies in few locations may hinder the operation of the system.In order to solve these problems,energy storage plays an essential role.The aim of this paper is to analyse the effects of the introduction of two possible alternatives as a way of energy storage:pumped hydro storage and electric vehicles.For this,we use a simulation model adapted to the features of La Palma,considering different scenarios.Results show that,in the most favourable scenario,the installation of an additional 25 MW from renewables(more than double the current power),supported by 20 MW of pumped hydro storage and a fleet of 3361 electric vehicles,would allow the current share of renewables to increase from11%(in 2015)to 49%.Furthermore,this would mean a 26%reduction in CO2 emissions,10%in costs of generated k Wh and 19%in energy dependence.

A Novel Design of Hybrid Energy Storage System for Electric Vehicles

In order to provide long distance endurance and ensure the minimization of a cost function for electric vehicles,a new hybrid energy storage system for electric vehicle is designed in this paper.For the hybrid energy storage system,the paper proposes an optimal control algorithm designed using a Li-ion battery power dynamic limitation rule-based control based on the SOC of the super-capacitor.At the same time,the magnetic integration technology adding a second-order Bessel low-pass filter is introduced to DC-DC converters of electric vehicles.As a result,the size of battery is reduced,and the power quality of the hybrid energy storage system is optimized.Finally,the effectiveness of the proposed method is validated by simulation and experiment.

Comparison of the topologies for a hybrid energy-storage system of electric vehicles via a novel optimization method

The combination of batteries and ultracapacitors has become an effective solution to satisfy the requirements of high power density and high energy density for the energy-storage system of electric vehicles.Three aspects of such combination efforts were considered for evaluating the four types of hybrid energy-storage system(HESS)topologies.First,a novel optimization framework was proposed and implemented to optimize the voltage level of a battery pack and an ultracapacitor pack for the four types of HESS topologies.During the optimization process,the dynamic programming(DP)algorithm was iteratively applied to determine the optimal control actions.The simulation results with DP were used to evaluate the energy efficiency of different HESS topologies at different voltage levels.Second,the optimized voltage level of the battery and ultracapacitor in each topology indicates that a higher voltage level usually results in a better system performance.The simulation results also illustrate that the optimized rated voltage level of the battery pack is approximately 499.5 V,while for the ultracapacitor pack,the optimized voltage level is at its maximum allowed value.Note that the constraint of the battery voltage is initialized at200–600 V.Third,the control rules for different HESS topologies were obtained through the systematic analysis of the simulation results.In addition,advantages and disadvantages of the four topologies were summarized through evaluation of the efficiency and operating currents of the batteries and the ultracapacitor.

Method of Electric Powertrain Matching for Battery-powered Electric Cars

The current match method of electric powertrain still makes use of longitudinal dynamics, which can’t realize maximum capacity for on-board energy storage unit and can’t reach lowest equivalent fuel consumption as well. Another match method focuses on improving available space considering reasonable layout of vehicle to enlarge rated energy capacity for on-board energy storage unit, which can keep the longitudinal dynamics performance almost unchanged but can’t reach lowest fuel consumption. Considering the characteristics of driving motor, method of electric powertrain matching utilizing conventional longitudinal dynamics for driving system and cut-and-try method for energy storage system is proposed for passenger cars converted from traditional ones. Through combining the utilization of vehicle space which contributes to the on-board energy amount, vehicle longitudinal performance requirements, vehicle equivalent fuel consumption level, passive safety requirements and maximum driving range requirement together, a comprehensive optimal match method of electric powertrain for battery-powered electric vehicle is raised. In simulation, the vehicle model and match method is built in Matlab/simulink, and the Environmental Protection Agency (EPA) Urban Dynamometer Driving Schedule (UDDS) is chosen as a test condition. The simulation results show that 2.62% of regenerative energy and 2% of energy storage efficiency are increased relative to the traditional method. The research conclusions provide theoretical and practical solutions for electric powertrain matching for modern battery-powered electric vehicles especially for those converted from traditional ones, and further enhance dynamics of electric vehicles.

Development Status and Application Analysis of Vehicle to Grid (V2G)

With the shortages of resources,environmental pollution,climate change,and other issues becoming more and more serious,it is extremely urgent to vigorously develop new energy vehicles.As the cost of batteries decrease year by year,the production and quantity of sales of electric vehicles(EVs)in the world,especially in China,increased substantially.In order to make vehicles to grid(V2G)technology better developed and applied in China.The brief introduction to V2G is given at first.Then the development status and specific cases of V2G at home and abroad are summarized.Finally,the problems that V2G may encounter during promotion and application in China are analyzed.Based on the development of the United States and Japan,specific policy recommendations are given in line with the basic national conditions of China.

某纯电驱动重载车辆能耗预测模型

高精度能耗预测模型是准确预测车辆续驶里程的重要前提。针对载荷大幅度变化且非结构化道路运行的纯电驱动重载车辆,建立其组合能耗模型,该模型由能耗计算基本模型与长短时记忆(Long Short-Term Memory,LSTM)神经网络差值修正两部分组成。基于能量流动过程驱动电机和变速器效率建模,结合汽车行驶动力学建立能耗计算基本模型;采用LSTM神经网络来修正基本模型能耗预测结果与车辆典型工况功率测试值的差值,有效提高了大幅变载荷且低信噪比坡度环境下的车辆能耗预测精度,因此组合能耗模型具有参数简单和模型拟合不需解释能耗规律的优点。经试验测试分析,与VT-Micro能耗模型和径向基(Radial Basis Function,RBF)神经网络能耗模型相比,所提组合能耗模型的功率预测平均误差率分别降低了17.76%和3.35%,能够实现纯电驱动重载车辆复杂工况下能耗的准确实时预测。

NiCo_(2)O_(4)//GO非对称超级电容器电动汽车动力系统应用仿真

将制备的NiCo_(2)O_(4)电极进行电化学性能测试,结果表明,NiCo_(2)O_(4)电极活性材料通过准可逆的氧化还原反应进行储能,表现出良好的电化学性能.进而使用Simulink仿真模拟了非对称超级电容器单体的放电过程,并使用AVL CRUISE仿真计算了超级电容器-锂离子电池复合储能系统的电动汽车行驶过程.结果表明,汽车在WLTC循环工况下的最大电池功率为38.0 kW,行驶时间为4.9 h,续航里程为224.4 km,相比单独的锂离子电池储能系统最大电池功率减小了31.3%,续航里程提高了11.4%.超级电容器对复合储能系统的电动汽车起到了平衡电池功率和提高续航里程的作用.