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In order to solve the problem of individual voltage unevenness of energy storage battery for electric power in series operation, a multi-level uniform conditioning circuit structure based on flyback transformation is proposed, which can effectively realize the individual voltage regulation of energy storage batteries for power grid. Individual battery current through the conditioning circuit, in the multi-level multi-directional flow process, at the same time without mutual influence, this scheme through the special high-precision multi-channel acquisition circuit module, in the charging process of equalization and floating charge stage, real-time acquisition of each cell accurate voltage value, according to the voltage value monitored, the single battery outside the preset voltage range is taken as the conditioning object. Select a group of three-year running battery pack, do the comparative experiment of adding conditioning circuit and no conditioning circuit, and carry out three-stage charging experiment of constant current and voltage changing, constant voltage changing current and floating charge. The experimental results show that the scheme can realize the rapid voltage correction of battery pack, improve the overall efficiency of battery pack, slow down the performance degradation speed, and extend the service life of the whole battery.

Aiming at the problems that the application of conventional energy storage batteries in DC distribution networks, such as high cost, complicated control, and post-maintenance, this paper proposes an adaptive control strategy for charging and discharging DC distribution network energy storage systems on the basis of retired batteries, and its port output voltage can change with the grid voltage fluctuations of the DC distribution network adaptively by building a set of direct-mounted bus-type energy storage system based on retired batteries, so as to realize the adaptive charging and discharging of energy storage batteries. Finally, when the network voltage of the DC distribution network system changes suddenly, the energy storage system can realize the adaptive charging and discharging function of the energy storage system by switching on and off the retired battery pack module, which is verified by the SIMULINK simulation and experiment platform.

Lithium battery (LiB) is widely used in electric vehicles (EVs), energy storage power stations and other fields. because of its high voltage, light weight, high energy density, good cycle performance, low self discharge rate and no memory effect, less environmental pollution and other significant advantages. However, due to the limited voltage and capacity of battery cells, battery is usually used as a battery pack composed of hundreds of single cells in parallel or series, The difference between batteries not only affect the charging and discharging capacity of batteries, but also lead to battery aging and potential safety problems. It is of great significance to study the influence of the differences between cells on the battery pack for battery grouping and battery balancing. This paper takes the coupling relationship among the initial state of charge (SOC), initial capacity and initial internal resistance into consideration, and establishes the relationship between the initial parameters. A model consists six cells connected in series is established based on the Rint equivalent circuit model, and simulations under different working conditions are conducted. The simulation results show that the consistency of the capacity of battery pack is mainly affected by the initial SOC and initial capacity. The influence of the two factors on capacity of battery pack consistency under different charging current rates is different. The initial internal resistance has little effect on capacity consistency under different charging current rates.

Lithium-ion batteries have been widely used in the field of energy storage, due to the high energy density, wide temperature range and long service life. However, in application, the parameters such as the capacity and voltage of each cell in the battery pack are inconsistent due to unreasonable use, poor operating environment and other factors. In this paper, the qualitative relationship between the voltage variation of lithium-ion battery and the cell capacity and SOC is firstly analyzed, and then an inconsistent cell identification method is proposed based on three feature parameters of voltage outliers, voltage range and voltage difference. The static component is obtained from the voltage in the unstable discharge data by empirical mode decomposition and the inconsistency of capacity and SOC of static components is analyzed. The online identification of inconsistency of lithium-ion battery pack is realized based on the threshold and $K$ -means algorithm.

Energy storage systems represents a critical role in power supply of electric vehicles (EV) and lithium-ion batteries is the most promising and dominant energy storage choice. Because of cell variations in a battery pack it is hard to obtain an accurate model to study the behavior of lithium-ion cells and in many situations different algorithms must be used to estimate state of charge. Several techniques for SOC estimation have been studied in the last years. These methods can be classified in three categories: direct methods, data-driven methods and state-observation methods. In this paper it is the intention to estimate state-of-charge (SOC) of lithium-ion battery using a state-observation method such as Kalman filter.The algorithm it is applied on an equivalent circuit model of a lithium-ion cell and after that can be extended to a pack of cells. Most of the time the performances are dependent on the measuring accuracy of current and open-loop calculation can lead to accumulated calculation errors due to uncertain disturbances from the practice application and lack of necessary corrective resolution.There are also other methods for estimating the SoC, like artificial neural networks, fuzzy logic, extended Kalman filtering based estimators but the main disadvantage of these methods is represented by the differences between each individual cell which are ignored most of the time. In this case for reliable and accurate results should take in consideration individual cell’s state, make calculation and the lowest SoC should be the reference point.

The need for vehicle electrification is growing across the world. However, increased cost and packaging volume considerations arising out of electrification, pose a major barrier to the adoption of electrified vehicles. One of the ways to alleviate cost and packaging volume concerns is through appropriate rating and sizing of the electric powertrain, which is influenced by several factors including power flow magnitude, energy storage capability, thermal limits, voltage and current limits, and packaging requirements. This paper presents practical powerflow considerations in the electric powertrain, associated challenges and potential directions towards reducing the cost and packaging volume of the e-drive system. The target vehicle segment considered for electrification in this study are twowheeled and three-wheeled road vehicles, which are dominant segments of India’s vehicle population. Electrification of this segment is expected to result in significant benefits, both for market penetration as well as the environment. The vehicle considered in the study consists of an e-drive system using a 48 V battery pack, connected to a three-phase power electronic inverter supplying a single electric machine for traction. Limits on e-drive system efficiency under these practical conditions for a range of torque-speed operating points are also discussed.

Electric Vehicle (EV) fleets have dramatically expanded over the past several years. There has been significant increase in interest to electrify all modes of transportation. EVs are primarily powered by Energy Storage Systems such as Lithium-ion Battery packs. Total battery pack capacity translates to the available range in an EV. State of Charge (SOC) is the ratio of available battery capacity to total capacity and is expressed in percentages. It is crucial to accurately estimate SOC to determine the available range in an EV while it is in use. In this paper, a Temporal Convolution Network (TCN) approach is taken to estimate SOC. This is the first implementation of TCNs for the SOC estimation task. Estimation is carried out on various drive cycles such as HWFET, LA92, UDDS and US06 drive cycles at 1 C and 25 {\deg}Celsius. It was found that TCN architecture achieved an accuracy of 99.1%., Comment: 17th IEEE India Council International Conference 2020

The heat dissipation and thermal control technology of the battery pack determine the safe and stable operation of the energy storage system. In this paper, the problem of ventilation and heat dissipation among the battery cell, battery pack and module is analyzed in detail, and its thermal control technology is described.

In recent years renewable energies are gradually being introduced to cope with issues accompanying with a rapid growth of the urban rail transit, such as tremendous energy consumption, serious carbon emission, limited capacity of the existing traction substations, etc. An energy conscious converter, combining a quasi-z source network based photovoltaic generation system and a high conversion ratio energy storage circuit, is proposed for the metro DC traction grid in this paper. The maximum power traction can be achieved through coordinated control between the LLC converter and quasi-z source network without additional conversion stages. The braking energy of trains can be recycled by the energy storage system besides absorbing the excessive solar energy. Adopting the presented modulation strategy in this paper, the gross voltage of batteries is no higher than one-fourth of the DC traction grid voltage. Therefore, fewer batteries need to be in series, which decreases the premature failure probability of the battery pack caused by the over- or under-charging of unbalanced individual cells.

Growing response for Electric Vehicles (EV) across the world is an implication of techno-economical efforts targeted to mitigate the challenges related to fossil fuels. Energy storage powering EVs is a very critical component. A battery pack used as energy storage in EVs uses many battery cells connected in series and parallel. These battery cells need close monitoring and management system during its operation in EVs. Such a system referred to as ‘Battery Management System’ (BMS) ensures a safe operating envelope while increasing battery power delivery capabilities and improving lifetime. The cell voltage balancing along with the State of Charge (SOC) and State of Health (SOH) monitoring are some of the critical functions of BMS. For EVs to become the best techno-commercial alternative for gasoline-based vehicles, BMS and battery packs will play a very crucial role. This paper highlights the state of the art of BMS and illustrates the passive cell balancing network design for Lithium-Iron-Phosphate (LiFePO4) batteries based on Digital Signal Processor (DSP) TMS320F28379D controller. Some key simulation and hardware results are presented to demonstrate the SOC estimation using the Coulombs counting method and battery cell balancing mechanism.

PHEVs have a high energy capacity battery pack which can only operate on electrical power for a given period. The battery pack can be recharged by a nearby socket. A novel combined bidirectional ac / dc adapter and dc / dc converter (henceforth combined converter) for PHEVs and electric / plugin electric conversions is introduced in this article. The integrated converter is capable of acting as an ac / dc battery adapter and of transmitting electrical energy between the battery pack and the high-voltage bus of the electrical traction network. It is seen that the integrated converter has a decreased number of high-current inductors and current transducers and has provided fault current tolerance for PHEV conversion.

According to the complex and changeable charging environment of mobile energy storage charging vehicles, this paper proposes an intelligent flexible charging strategy based on queuing theory for the single control strategy of traditional mobile energy storage charging vehicles. This strategy takes the optimal charging time as the optimization goal and dynamically adjusts the output power of the charger. At the same time, flexible charging also involves DC / DC module parallel current sharing and other issues. In this paper, a DCDC converter is used to control the charge and discharge of the battery pack. A charge and discharge controller for the energy storage battery pack based on PI control is designed. The energy storage battery pack During the charging process, the current closed-loop control realizes constant current charging, and the voltage outer loop current inner loop double closed loop control realizes constant voltage charging; during the discharge of the energy storage battery pack, the double closed loop is used to stabilize the battery pack discharge voltage, which is established in the Matlab environment The simulation model of charge and discharge of energy storage battery pack was obtained, and the simulation results verified the correctness and feasibility of the battery pack structure and control strategy.

A Smart Energy Management System (SEMS) for a Highly-Integrated Battery-Ultracapacitor system (HIBUC) is presented in this paper. The proposed SEMS consists of driving the Battery Pack (BP) in order to fulfill the base part of the overall HIBUC power profile, while the Ultracapacitor Module (UM) shaves the residual power peaks to the maximum extent. In addition, BP has the task of driving the UM energy content properly in the medium/long-term, which may deviate in the short-term due to unexpected power fluctuations and/or unmodelled system losses. As a result, UM prevents BP from frequent and sudden power variations, while BP ensures its continuous operation. The effectiveness of the proposed SEMS has been preliminary verified through numerical simulations, which refers to the case of an experimental HIBUC prototype.

Recently, Electric Vehicles (EVs) are becoming more widespread. However, their mass adoption is hindered by the limited capacity of their Energy Storage System (ESS). Nowadays mainly Lithium-ion (Li-ion) technology is used for mobile applications, however, their energy density and cost put a hard limit on the maximum size of viable EV battery packs. Therefore, it is crucial to use existing technologies as effective as possible. To efficiently use a battery pack over its entire lifetime, the State of Health (SoH) of the cells needs to be taken into account. In this paper, we propose a novel SoH estimation method, based on the battery pack’s behavior during Active Charge Balancing (ACB). From this behavior we are deriving a metric and show that it strongly correlates with the SoH. We use this metric, together with other cell parameters, to train a Random Forest (RF) regression estimator. To gather the training data, we implemented a modular simulation framework, that is able to reproduce the charging and discharging cycles, the charge balancing processes, as well as the aging behavior of battery packs over their entire lifetime. Besides showing a strong correlation between balancing behavior and SoH, we are able to estimate the cells’ SoH with an accuracy of 1.94 % for the capacity and 4.28 % for the resistance, respectively. Our capacity SoH estimation outperforms state-of the-art machine learning approaches, while we are among very few to even provide an estimate for the resistance with a high accuracy.

In order to ensure the good operation and long life of the lithium battery pack, the parameters of the battery pack must be tested, managed and controlled reasonably and effectively. Therefore, based on the intelligent detection chips STM32F103C8T6 and BQ76930, the lithium battery test platform was designed. The platform saves a lot of devices, simplifies the circuit and consumes less energy. It also has small volume, low price and other advantages. The battery current, voltage and temperature are detected by BQ76930, OVC and SOC of battery pack are estimated by STM32F103C8T6, and the battery characteristic parameters are displayed by upper computer. All of these can be used as the basis of battery fault diagnosis and danger judgment. In addition, the detection platform also set threshold protection to improve the security of the platform.

Battery based energy storage systems find a wide array of applications from electric vehicles to power grids. This paper presents a new circuit topology for cell-to-cell active balancing of their battery packs. Its simple control scheme is developed and presented in detail for online operation. The design is modular and does not require a custom multi-winding transformer, instead, relying on a bidirectional synchronous buck converter and two energy storage elements. Also, only four sensors are necessary to implement its current-control scheme. Simulation is carried out to demonstrate the speed and efficacy of the proposed technique.

This paper studies a thermal runaway warning system for the safety management system of lithium iron phosphate battery for energy storage. The entire process of thermal runaway is analyzed and controlled according to the process, including temperature warnings, gas warnings, smoke and infrared warnings. Then, the problem of position and threshold setting of the warning sensors are studied. Finally, a hierarchical warning system is established and a communication architecture diagram of system warning is constructed. It is shown that the system can quickly locate the area where the battery pack is out of control, and quickly perform corresponding disconnection, firefighting and alarm operations to ensure the safe and stable operation of the battery storage power station.

The equalization system is a key technology in the large-capacity energy storage management system. The existing active equalization and passive equalization can only control the capacity and voltage deviation inside the module (cluster). Although the balance of the SOC in the cluster is realized by the transfer or consumption of the energy in the batteries, the system topology of the large-capacity energy storage is complex and the number of batteries is large. For the entire energy storage system, the overall SOC balance must be considered especially when the system power output demand is close to or exceeds the rated power of the system. The short board cluster will limit the output power capabilities of the overall system. Aiming at the SOC balance of large-capacity energy storage system, this paper allocates the power command sent by the energy storage controller to the energy storage system according to the SOC weighted control algorithm of the fuzzy logic control theory. Through the power control of the bidirectional DC/DC converter, the battery pack whose cluster SOC value is higher than the average value discharge more power in the discharge phase, and the battery pack with SOC value lower than the average value absorbs more energy in the charging stage, resulting the capacity consistency of the battery clusters. Also, the specific implementation steps achieving the SOC weighed control based on Fuzzy logic theory has been illustrated in detail.

In the article the authors presented the traction battery modeling concept on the basis of the single cell exploitation analysis. This process is carried out with the use of load data obtained in real, theoretical or standardized conditions and real exploitation data of chemical cells obtained on a dedicated research stand. The proposed method of scaling was checked by comparing the characteristics of nominal capacity of the single cell and battery pack dedicated to this research. In order to additionally check the validity of the concept, thermovision tests of temperature distribution in the battery pack were carried out.

The use of battery energy storage systems has gained wider attention in many sectors such as: power system, automotive, aircraft, oil and gas, among many others during the recent years. However, the association of batteries in a bank without the proper control may lead to problems to the batteries such as voltage imbalance, uneven degradation and incompletely use of the whole potential of the battery bank. This paper introduces a new concept of battery charger topology, named herein as SmartBattery, which is composed of a two-stage dc/dc converter integrated upon each battery pack. This solution allows each battery unit to be charged/discharged with different current profiles, even when they are series-connected. Then, this paper proposes a coordinated control strategy to balance the battery units in different stages of degradation and/or states of charge, without the need of bypassing any storage unit. Simulation results are performed to verify the equalization among batteries in a bank with different ages or states of charge during charging and discharging processes.

Electric Vehicles (EVs) are powered by a large number of battery cells, which must be managed effectively/efficiently to deliver the required power/energy during their warranty period. An EV’s operation requires large and fluctuating power from its battery pack, but its battery cells have only limited tolerance to (dis)charge stress, accelerating their degradation. Moreover, battery cells have different (dis)charge stresses depending on their physical positions in the battery pack, causing different degradation rates and thus the unbalanced State-of-Health (SoH) or State-of-Charge (SoC). To address this problem, we design, implement and evaluate a novel energy storage system with energy buffers and an SoC-balancing circuit, to extend both the battery life and EV’s operation-time. We first design a hybrid energy storage system that efficiently meets the EV’s representative power requirement. We then develop an optimal power distribution to minimize the EV’s energy consumption and its battery cells’ stress. We prototyped and evaluated this solution, demonstrating a reduction of discharge/charge stress by about 21.8%, and thus extending battery lifetime while balancing cells’ SoC.

Electric vehicle (EV) batteries typically retained around 70- 80% of their initial capacity at the end of their automotive life. The first batches EV batteries are hitting their retirement age and around 3 million used battery packs will be coming out from EV annually which represent around 108 GWh. Automotive companies and OEM have announced numerous projects and business models for second-life batteries, such as the stationary energy storage system (ESS) to extract additional services and revenue in post automotive life with cross-cutting benefits. The potential of second-life batteries lies in their state of health (SoH) or remaining useful life. To enable this market for second use batteries, it is necessary to demonstrate the capability of such batteries in real-world scenarios and validating the longevity of these batteries in this application is critical. This paper characterises three selected Nissan Leaf Cells/Modules disassemble from 24 KW Nissan Leaf pack that reach an end of life (EoL). The modules are tested individually to provide insight into the variation in degradation across a single battery pack and also establish the available energy at EoL via Hybrid pulse power characterization (HPPC). The result shows three data points of capacity and Ohmic resistance. Furthermore, the batteries achieved the power density of 700 W/Kg/300 W/Kg during discharge/regen in the working regions from 100% to 30% and /80% to 20% DOD respectively. Besides, the HPPC micro cycle discriminates between the strong and weak battery in 120 s.

In Electric vehicles, the Li-ion battery reaches its end of life when the capacity is decreased to 80% of the initial rated capacity. However, a battery with only 20% used capacity does not mean the battery cannot be used in a secondary application with less current demand, in a controlled and secure environment. This necessitates a comprehensive understanding of the configuration of the end of life (EoL) batteries in module and pack level, in terms of inconsistencies in capacity and impedance of the cells forming the module and hence the battery pack. Accordingly, a safer and longer second life use can be granted. This paper investigates the impact of parallel connection on the impedance and capacity of four, pouch lithium-ion cells forming a battery module in 2P 2S configuration. The energy storage capacity and the AC impedance of each parallel pair and individual cells are recorded and compared. The results highlight that the capacity loss due to the parallel connection is 6% less than the sum of the individual capacity for each cell. With the help of a developed equivalent circuit model, the ohmic resistance of the pair and cell is estimated to demonstrate the contribution of interconnections in increasing the total impedance and hence the perceived loss of capacity in the parallel connection.

The energy market is becoming more and more complex, and various harmonics and distributed energy have impacted the large power grid. Various factors have led to the need for more scientific and rational allocation of energy, so as to achieve continuous and reliable operation of the system. Realizing the control of energy storage systems to make them reliable and efficient has gradually become a huge challenge for modern power systems. Large-scale advanced battery energy storage technology faces the limitations caused by battery cell inconsistency, and the highly integrated and intelligent control of the equalization circuit is the solution to this problem. In this paper, by improving the structure of the traditional buck-boost circuit, a multi-input and multi-output converter which is easy to expand is proposed to realize the energy transfer between the individual cells of the battery pack. At the same time, the graph theory model of the equalization circuit is established. The efficiency of the related circuit is compared and analyzed through simulation and experiment. Finally, the superiority of the novel circuit topology proposed in this paper is verified. Simplify the practical problems of complex engineering into simple graphs in graph theory, so that comparisons under the same dimension can be easily obtained to obtain the merits and demerits of each method.

Compared with ordinary lead-acid batteries, lithium batteries are gradually favored by more electric bicycle manufacturers due to their high energy density, high charging and discharging efficiency and other properties. In order to ensure that the operating status of the rental battery pack applied to electric bicycles can be monitored by the operating units in real time during charging or discharging, a lithium battery management system for electric bicycles is designed. The battery management system can monitor the voltage, current, temperature, energy storage and location information of the battery pack in real time, and transmit information to the cloud management platform in real time. The system has been used in the leasing battery products of a battery leasing enterprise.

Valve regulated lead acid (VRLA) batteries widely used in substations still have large residual capacities when they are retired, so they can be reused in battery energy storage systems (BESS). A reusing BESS for retired VRLA batteries is designed in this paper, and its main function is peak-load shifting. The scale of this reusing BESS is 187 kW/1.87 MWh, and 3120 retired VRLA batteries are used. The reusing BESS can be divided into five sub-BESSes. Each sub-BESS is arranged in a container and consists of six parallel battery packs. Each battery pack consists of 104 battery cells in series, and it is connected to the main grid through a power conversion system (PCS). Meanwhile, each battery pack is managed by a battery management system (BMS). The BMS can achieve the functions such as battery dynamic equalization, overvoltage/undervoltage protection of each battery cell, and automatic isolation of defective batteries. Finally, the advantages and disadvantages of this reusing BESS are demonstrated by comparing it with another design of the reusing BESS, and the economic performance of this reusing BESS is evaluated.

Typical solar powered DC-microgrids (DCMG) employ rechargeable batteries for energy storage. In order to extract and deliver the maximum power out from the PV array to the load, maximum power point tracking (MPPT) solar charge controller is mandatory. With the commercial supercapacitor (SC) devices available in the market, new converter techniques with SC energy storage are possible for DCMG systems. The SCALED converter is such a technique where the rechargeable battery bank is replaced by a supercapacitor bank. However, if a SC bank is used as the sole energy storage, existing MPPT schemes are no longer appropriate since the storage bank acts as near ideal capacitor instead of a rechargeable battery pack. This is due to the fact that a capacitor bank retains energy within its electrostatic field, compared to the electrochemical reaction related back EMF of a battery pack. This paper presents the theoretical analysis to validate the above hypothesis.

A simplified mathematical model of supercapacitor-battery hybrid energy storage in voltage analysis was established. Make full use of the battery's high energy density, low cost and high power density of the supercapacitor, and the advantages of long cycle time complement the power supply, greatly improving the performance of the system to improve the voltage. A new balanced charging and discharging topology and control strategy are proposed to enhance the performance and extend the service life of the battery pack. On the Matlab platform, the simulation calculations are given for the given examples. The simulation results show that the grid connection of the hybrid energy storage device can effectively improve the voltage stability of the system.

Lithium-ion batteries play an important role in large-scale energy storage systems. However, the power inconsistency of the battery packs restricts the developments of modern technologies in energy storage area. The motivation of the present study is to serve the growing needs of the energy balance for lithium-ion battery packs. The present study proposes a flexible multiphase interleaved converter for the energy equalization of a lithium battery pack with series configuration. Moreover, the graph theory is applied to the analysis of equalization circuits. It is intended to establish a unified standard for the comparison. The parameter of average efficiency is considered as an important indicator to evaluate the characteristics of the equilibrium system. The proposed method is verified by constructing a lithium-ion battery pack with the equalization circuit. It is observed that the proposed multiphase interleaved converter has flexible characteristics, while it has low energy loss compared with the conventional methods. It is found that the proposed method simplifies the complex equalization circuits into graphs and facilitates the comparison of the average efficiency of the system. It is concluded that this method is a feasible and powerful method for evaluating the battery equalization circuit. This approach can be applied for solving complex problems in other engineering applications.

The integration of cells that exhibit differing electrical characteristics, such as variations in energy capacity and internal resistance can degrade the overall performance of the energy storage system (ESS) when those cells are aggregated into single battery pack. When cells are connected electrically in parallel, such variations can lead to significant individual differences in battery load current, state of charge (SOC) and heat generation. Further, if consideration is given to small variations in cell interconnection resistance, the detrimental effect on load imbalance is amplified. Given that cell resistance is known to be a function of both SOC and temperature, the impact of the imbalance is compounded as the performance of cells further diverge under load. During extended periods of excitation, variations in cell depth of discharge (DOD) and the occurrence of temperature gradients across the parallel connection will accelerate cell ageing and, if unmanaged, may present safety concerns such as the onset of thermal runaway. In this paper the impact of varied SOC and temperature on the overall performance of the ESS with parallel connected cells has been investigated. The results highlight that 8% variation in the initial SOC can result in a current difference of 62% among the cells, while a temperature variation of 8°C results in a current deviation of 14%. Moreover, it was found that the interconnection resistance can significantly increase the inhomogeneity.

Lithium battery pack is the smallest unit of energy storage system. Due to differences in manufacturing processes and usage environments, it is easy to cause the battery unit to be unbalanced, affect the overall performance of the battery pack and increase the safety hazard of overcharging and over discharging of the battery after long-term use. In this paper, the battery state of charge is used as the equalization variable, and the bidirectional flyback converter is used as the energy transfer circuit. A bidirectional active equalization control strategy is proposed for the energy storage lithium battery pack. The fuzzy PI controller is designed to optimize the equalization current, thus improving the equalization speed and efficiency. The equilibrium simulation model is built in MATLAB. The equilibrium results verify the effectiveness of the control strategy.

Electrification of transportation and energy storage systems is accelerating the advent of battery “systems of systems.” Due to high complexity thereof, a number of challenges exist in battery management such as charge balancing and anomaly detection. Internal short circuit (ISC) is one of the most common and hazardous anomalies, and a few methods have been proposed to detect it inside a serial-parallel (two-dimensional) battery network. This paper extends the previous work and proposes a novel concept of three-dimensional battery packs. It follows the industry practices of constructing a pack from modules consisting of batteries, but use of an extra dimension and additional current paths enhance ISC detectability with the minimal use of current sensors. This paper reports ISC simulation results from the proposed 3D battery pack topologies.

Hybridization of the energy storage system in an electric vehicle offers the flexibility to dimension energy content and power capability independently. The proposed hybrid energy storage system, with one dc-dc converter, connecting either the high energy or high power pack with the inverter dc-link, can lead to weight and volume savings in comparison to a single battery pack topology. An energy management system controls the power flow. This paper presents a tool for the design and simulation of hybrid energy storage systems. Dynamic programming is used to optimize the power flow for the overall system efficiency. Multiple scenarios are presented to show the influence of the driving profile on the efficiency of the storage system in an electric vehicle designed for high power racing applications.

Battery energy storage systems have been widely used in modern power systems. However, for a complex system with huge amount of batteries, the healthy, reliability and safety is still a big challenge. During the work of these systems, while one or several individual cells deteriorate or even broken, the entire battery pack will be affected. Fortunately, with the development of IOT technologies, an increasingly large amount of data can be collected from energy storage stations. Such data may be useful to understand battery status with certain big data tools. In this paper, k-means and DBSCAN clustering algorithm are introduced to identify and deteriorated batteries. Three parameters are proposed from the battery data, as an input model of clustering algorithms. The number of clusters and weight assignment are also adjusted considering battery’s special properties. The research used a lead-carbon energy storage system in establishing the method in the proof of concept work. As the result of clustering, an analysis of battery pack’s consistency was revealed and aged batteries were located. At the end, we verified the results by comparing the charging voltage curves of the batteries. This method may help the researcher to find deteriorated batteries in an easy way.

Nowadays, a large variety of lithium-ion battery (LIB) configurations are being developed in order to meet the specific requirements of different applications, e.g., for battery electric vehicles or stationary energy storage. One characteristic parameter of LIBs is their internal resistance, as it influences the system’s power capability and heat generation. However, determining the resistance of a battery pack is not trivial, since it is dependent on many intrinsic and extrinsic influencing factors. In this work, influencing factors on the resistance of 18650 cylindrical cells and large-size prismatic cells are quantified experimentally by means of direct current (DC) pulses and electrochemical impedance spectoscropy (EIS). Furthermore, challenges involved in characterizing the resistance on higher system levels are addressed by investigating battery modules and packs of a research vehicle built out of small cylindrical cells and a series vehicle with large prismatic cell architecture. Finally, based on experimental findings, the authors derive implications for battery modeling that make it feasible to choose the suitable modeling depth and evaluate the numerous different available cell types and system configurations efficiently for their suitability for different battery system concepts. The data for all evaluated resistances is provided as supplementary material [1].

Electrical energy storage is widely used not only in the mobile applications but also in stationary applications as like uninterruptable power supply. An energy storage system with the high energy density and high-power capability is very important for some specific applications like electric vehicles (EV). Lithiumion-batteries are well known for their high energy density while super-capacitors have high power capability. Lithium-ion capacitors (LiCs) which are a hybrid energy storage technology consisting of the lithium-ion batteries (LIBs) and super capacitors (SCs), combine the advantages of LIB and SC and eliminate their negative properties. However, the reliability of all types of energy storage technologies including LiCs can be drastically affected by overheating issues. These issues are more likely to happen in the closed casing battery pack. In this research, many experiments are performed to investigate the effect of current magnitude on the temperature distribution pattern in a module of 12 LiC cells. Then, in the COMSOL Multiphysics environment, a numerical solution is designed for a brief study of temperature distribution. The presented model accounts for different heat sources without getting into an electrochemical model. The simulation result shows a good agreement with the experimental results with an error of less than 5%. The presented model can be used to design a thermal management system with the focus on the hottest parts of the module.

This paper portrays the benefits of introducing an ultracapacitor into a battery pack of an urban electric vehicle drive train. Simulations are done taking two basic scenarios into consideration: fresh cells and half-used battery cells. The simulations show that the lower the temperature higher the hybrid system efficiency. Data from real world are considered to conduct this study. Simulations are done considering modified Bangladeshi drive cycle for low weight vehicles. Several issues like volumetric, gravimetric and cost issues of hybridization are present in this paper. By this system the power loss of the system can be reduced by up to 5% to 10%. Finally, hybridization not only increases the efficiency of the energy storage system also increases the power train efficiency and battery lifespan. This paper would help researchers for further development of this topic.

In view of the grid connection of the traditional composite energy storage electric vehicle system, the energy is usually provided by the battery pack alone, a new type of energy feedback grid-connected system was designed to optimize the ability of the battery pack to output high current and extend the life of the energy storage system. In this paper, the structure and working principle of the new energy feedback grid connected system are analyzed, and the battery and supercapacitor are modeled in detail, realize the requirements of variable power grid connection for energy storage through energy management strategy. The inverter is controlled by VSG technology as a synchronous generator to ensure the reliability of energy transmission and reasonable power distribution automatically, to realize the rapid compensation of unbalanced power and the state of energy storage capacity adjustment. It can simulate the inertia and damping characteristics of synchronous generators, overcome the influence of traditional inertialess connected inverter on the power grid, and can effectively improve the ability of the grid to accept renewable energy. Finally, the feasibility and effectiveness of the control method are verified by simulation model. The research results can provide reference for the safety control of the new energy electric vehicle grid-connected system.

The application of modern energy storage is the cornerstone of the development of energy Internet technology, and energy storage components play an important role. However, the use of lithium batteries as energy storage components is also facing application challenges, among which the impact caused by battery inconsistency is particularly critical. A forced equalization circuit is proposed in this paper, which can transfer energy from any battery to other batteries in the battery pack, thereby reducing the inconsistency of each energy storage unit and prolonging the life of the battery pack. The Nash equalization based on the complete information game strategy is used to optimize the control of the circuit. In theory, the low loss is achieved while fast equalization. Finally, the simulation model is built to verify the working principle and equalization strategy of the circuit. The results show that the control method using Nash equalization can effectively improve the circuit efficiency.

The configuration of isolated microgrids is of great significance for military outliers built in remote islands and high mountains. To address practical concerns, mobile energy storage system and shiftable load are specifically introduced to represent military battery pack and oxygen generation/seawater desalination unit, respectively, in this study. Then an optimal configuration model for isolated microgrids with multi-objectives is proposed, and it is tackled with an improved preference-incentive co-evolution algorithm (PICEA-ng). Numerical simulation validates the effectiveness of our proposed model and algorithm based on practical data. Finally, the role of the mobile energy storage and shiftable load on influencing the optimization objectives of the microgrid system is analyzed.

A Highly-Integrated Battery-UltraCapacitor system (HIBUC) is presented in this paper. It consists of a battery pack and an ultracapacitor module, which are coupled to each other through a three-level neutral-point-clamped converter. The latter is connected to the point of common coupling between a microgrid and the main electric grid through a step-up transformer, which enables lower DC-link voltage rating and, thus, eases HIBUC prototyping without affecting its performances significantly. The DC-link is also connected to a dissipative voltage regulator, which has been designed with the dual purpose of preventing DC-link overvoltage and improving DC-link voltage regulation simultaneously. The effectiveness of the proposed configuration has been verified through a simulation study, which has been carried out in the Matlab-Simulink environment and refers to different HIBUC operating conditions.

Lithium-ion batteries are becoming the main energy storage in electric vehicles and electric grids. To elevate the battery capacity and the voltage supply, the battery cells are stacked to form a battery pack. The state-of charge (SOC) of the battery pack requires continuous monitoring for the operation safety. The current developed SOC estimation algorithms shows decent estimation accuracy but they are designed for individual cells. These algorithms stay in the battery cell level because they cannot capture the cell-to-cell difference which exists after manufactured. This paper proposed a battery pack SOC Co-Estimation algorithm based on the estimated battery cell SOC. The proposed battery pack SOC Co-Estimation algorithm can accurately estimates the SOC of a battery pack with three serial connected battery cells but without cell balancing. This algorithm also has the potential to reduce the computation effort on the battery management system (BMS) because it does not need to monitor every single cell in the battery pack.

Battery packs with a large number of battery cells are becoming more and more widely adopted in electronic systems, such as robotics, renewable energy systems, energy storage in smart grids, and electronic vehicles. Therefore, a well-designed battery pack is essential for battery applications. In the literature, the majority of research in battery pack design focuses on battery management system, safety circuit, and cell-balancing strategies. Recently, the reconfigurable battery pack design has gained increasing attentions as a promising solution to solve the problems existing in the conventional battery packs and associated battery management systems, such as low energy efficiency, short pack lifespan, safety issues, and low reliability. One of the most prominent features of reconfigurable battery packs is that the battery cell topology can be dynamically reconfigured in the real-time fashion based on the current condition (in terms of the state of charge and the state of health) of battery cells. So far, there are several reconfigurable battery schemes having been proposed and validated in the literature, all sharing the advantage of cell topology reconfiguration that ensures balanced cell states during charging and discharging, meanwhile providing strong fault tolerance ability. This survey is undertaken with the intent of identifying the state-of-the-art technologies of reconfigurable battery as well as providing review on related technologies and insight on future research in this emerging area.

The fluctuating nature of solar power generation Makes the coupling of energy storage and solar energy inevitable. This paper explores the integration of all the typical components of a PV-battery system in one single module, introducing a prototype of the so-called PV-Battery Integrated Module (PBIM). The electrical and thermal performance of the prototype were studied in order to analyse its behaviour under severe testing conditions. The prototype exhibited an appropriate charging efficiency of 95.7% on average, while the battery pack operated safely (at less than $45^\circ\mathrm {C}$). When compared to a conventional system (battery and charge controller in a separated manner), the mean solar panel temperature of the prototype was 9.34% higher. However, in terms of power, the thermal losses in the PBIM resulted in an average increase of just 1.3 W (4.6%) in comparison to a conventional system. The testing validated the applicability of the integrated concept in harsh conditions, providing valuable information for future design improvements.

In electric vehicles the energy storage provided by the batteries is of utmost importance: it provides autonomy to the vehicle. However rechargeable batteries cannot operate alone, a Battery Management System is needed to provide safe operation conditions, monitor its state and balance its charge. In this article a Battery Management System is developed for applications in electric vehicles and autonomous robotics. We design the system in a modular way to give flexibility and allow portability to different type of battery packs. Low-cost microcontrollers were used for the system providing also communication with the vechicle's on-board computer. A passive balancing schemed is chosen as a way of battery balancing. The proposed system was tested using a battery pack demonstrating its balancing capabilities.

We present a hybrid simulation and a real-time test platform for developing control systems for photovoltaic (PV) inverters with integrated battery energy storage (BES). The platform consists of a dual-stage single-phase PV inverter system, DC coupled with a full-bridge grid connected inverter, which emulates the charge regulator and battery bank. The real-time control of the two power electronic converters is implemented in a Simulink/dSpace platform, together with the real-time simulation model of the battery pack. The input power can be provided by either a high performance PV emulator or by a physical PV array. The platform enables real-time testing of PV$+$textbf{{BES control systems and energy management systems (EMS), for a variety of battery technologies, which can be modelled in detail and emulated by the full-bridge grid connected inverter. Such flexibility is difficult to achieve with real BES systems, due to electrical safety and cost constrains of high power charge regulators and battery packs.

The consistency tests of power Li-ion batteries which were good capacity, internal resistance consistency, and initial open-circuited potential were researched. The results showed that the monomer capacity consistency has a more significant impact on the capacity of series-connected battery pack, the capacity of battery pack is equal to the minimum capacity of single series of batteries — short board effect, the monomer battery capacity declines, causing the capacity of whole battery pack decrease proportionally. The voltage dispersion in later charging and discharging stage also increases with the capacity difference. And according to the analysis of the difference in voltage among 4 discharged batteries, at a normal temperature, the consistency among the batteries goes down at the end of the discharge process, while with the decrease in temperature, the consistency among the batteries goes down throughout the discharge process.

The aim of this contribution is to study the driving load on electric vehicles through data mining methods. The battery pack is currently the major cost driver for these vehicles. Thus, battery durability is an important lever to economically establish electric mobility in the mass market. A segmentation modelling approach, based on unsupervised clustering algorithms, evaluates battery management system field data from BMW i3 vehicles such as state of charge, temperature and current in terms of their historical distribution. Clustering algorithms, due to their frequent use in the field of machine learning and information retrieval, are able to analyse big quantities of vehicle data with the aim to group vehicles with similar driving behaviour. The cluster analysis is further validated using the method of calculating respective silhouette coefficients to assess clustering performance and the influence of input parameters. The analysis of histograms concludes with the definition of the most common types of drivers worldwide. The vehicle clusters can further be correlated with battery ageing in order to find suitable 2nd life applications as part of stationary energy storage systems.