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This paper investigates the role of artificial neural networks in enhancing the accuracy of instantaneous power estimation of electric vehicles’ batteries. In electric vehicles, a battery is used as a main or complementary bidirectional power source. To optimize the energy management of the vehicle, the power sourced or sinked by the battery must be estimated in real time under any condition. The power of the battery is a function of many variables including the current, the state of charge, the ambient temperature, and the state of health. This paper evaluates some existing equivalent circuit models for estimating the instantaneous power of electric vehicles' batteries and proposes new artificial neural network-based models to enhance the power estimation accuracy. The experimental data obtained by performing standardized electric vehicle tests using a 3.6-V/16.5-Ah lithium-ion battery cell and a 12.8-V/150-Ah lithium-ion battery pack are presented and used for models' evaluation. [ABSTRACT FROM AUTHOR]

Conventional energy generation sources mainly provide energy supply to remote areas nowadays. However, because of growing concerns over greenhouse gas emissions, the integration of renewable energy sources is mandatory to meet power demands and reduce climatic effects. The advancements in renewable generation sources and battery storage systems pave the way for microgrids (MGs). As a result, MGs are becoming a viable solution for power supply shortage problems in remote-area applications, such as oceanic islands. In this paper, an islanded MG, which consists of PV system, tidal turbine (TT), diesel generator (DG), and Li-ion battery, is considered for Ouessant island in Brittany region in France. The economic operation of the MG is achieved by including battery degradation cost, levelized costs of energy of the PV system and TT, operating and emission costs of DG, and network constraints. The developed model leads to a non-linear and non-convex problem, which unfortunately can converge to a local optimum solution. The problem has, therefore, been relaxed and converted to a convex second-order cone model to achieve an optimal decision strategy for islanded MG operations with a global or near-global solution. Numerical simulations are carried out to prove the effectiveness of the proposed strategy in reducing the operating and emission costs of the islanded MG. It is shown that the developed convex energy management system formulation has an optimality gap of less than 1% with reduced computational cost. [ABSTRACT FROM AUTHOR]

Compared with the conventional hard switching battery equalizers, hierarchical battery equalizer based on the bipolar continuous-conduction mode buck–boost units could effectively reduce the switching loss and improve the conversion efficiency. This paper mainly addresses the key technical challenges associated with the optimal design of this battery equalizer. The inductor current is controlled to enter into the negative region. Thus, the mosfet body diode provides a freewheeling path for the inductor current during the dead band. This ensures zero-voltage switching turn-on of both power mosfets in each buck–boost unit without auxiliary snubbers. Therefore, the switching losses are significantly reduced. Meanwhile, the integral of the inductor negative current is precisely controlled to minimize the circulating current. This guarantees both minimized conduction losses and suitable equalization speed. Furthermore, an equalization algorithm, which compensates the battery internal resistance induced state-of-charge error, is proposed to improve the equalization accuracy. The operating principles and design considerations are analyzed in detail. An experimental prototype to balance four series-connected lithium-ion battery cells is implemented. The experimental results validate the design of the equalizer and demonstrate obvious efficiency enhancement over the conventional method. [ABSTRACT FROM AUTHOR]

Microgrid protection schemes require a fast, reliable, and a robust communication system, to adjust relay settings for the appropriate current levels according to the microgrid's operation mode. However, risks of communication link failures and cyber security threats are major challenges for the implementation of protection scheme. This paper presents a co-simulation platform for microgrid based on multiagent system (MAS) when the communication is available in the system. IEC 61850 is used to emulate the proposed protection scheme. The data distribution service (DDS) middleware is used to link between the hardware and software environments. During islanded mode, the system is capable of riding-through communication failures by the aid of a lithium-ion battery. When the communication is attacked, the battery plays an important role and contribute to the fault current for helping the circuit breaker to trip during islanded mode. The design of the control algorithm for the battery's ac/dc converter is developed with single mode operation to eliminate the reliance on communicated control command signals to shift the controller between different modes. [ABSTRACT FROM AUTHOR]

This paper develops a state-of-charge (SOC) estimation model for a lithium-ion battery using an improved extreme learning machine (ELM) algorithm. ELM is suitable for an SOC estimation since the ELM algorithm has fast estimation speed, good generalization performance, and high accuracy. However, the performance of ELM is highly dependent on training accuracy and the number of neurons in a hidden layer. Hence, a gravitational search algorithm (GSA) is applied to improve the ELM computational intelligence by searching for the optimal value hidden layer neurons. The optimal ELM-based GSA model does not require internal battery knowledge and mathematical model for an SOC estimation. The model robustness is validated at different temperatures using different electric vehicle drive cycles. The performance of the ELM-GSA model is verified with two popular neural network methods: back-propagation neural network (BPNN) and radial basis function neural network (RBFNN). The results are evaluated using different error rates and computation costs. The results demonstrate that the ELM-based GSA model offers a higher accuracy and lower SOC error rate than those of BPNN-based GSA and RBFNN-based GSA models. Furthermore, a detailed comparative study between the proposed model and existing SOC strategies is conducted, which also demonstrates the superiority of the proposed model. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries are characterized by having a very good performance in terms of efficiency, lifetime, and self-discharge, which allowed them to become the major player in the electric vehicle (EV) applications. However, they were not able to totally overcome the EV range anxiety. Thus, a research is carried out nowadays to develop batteries with even higher gravimetric energy density, which should allow a substantial range increase. One of the technologies, which should be able to meet the range requirements is the lithium–sulfur (Li–S) battery. Thanks to the extensive research and development efforts, these cells are close to enter the market, being evaluate in various projects. In this paper, we have proposed an electrical circuit model for a Li–S pouch cell, which was parameterized based on extensive electrochemical impedance spectroscopy measurements. The developed model was verified using static and pulse discharge profiles, showing a good accuracy in predicting the voltage of the tested Li–S battery cell. [ABSTRACT FROM AUTHOR]

This paper is focused on determining the efficiency dependency on the switching frequency for a solid state transformer (SST) with one of the ports connected to an energy storage device (Lithium-Ion battery). Some contributions for measuring the efficiency/losses for different power converter structures for energy storage applications can be found in the literature. However, there are few references which consider the impact of the high frequency behavior of the battery in the complete system performance. Moreover, to the best of the authors’ knowledge, there is no study considering these effects when the energy storage system is directly coupled to an SST port. This research will first obtain parametric high frequency models of the battery cells and modules, the SST, and the power converter based on a vector fitting method in frequency domain. The models will be used to evaluate the system losses depending on the converter switching frequency and the dc-link capacitance. Experimental results confirm the accuracy of the proposed model as well as the battery losses dependency on the switching frequency, the dc-link capacitance and the state of charge. [ABSTRACT FROM AUTHOR]

In this paper, an artificial neural network (ANN) based approach is proposed to estimate the capacity fade in lithium-ion (Li-ion) batteries for electric vehicles (EVs). Besides its robustness, stability, and high accuracy, the proposed technique can significantly improve the state-of-charge (SOC) estimation accuracy over the lifespan of the battery, which leads to more reliable battery operation and prolonged lifetime. In addition, the proposed technique allows accurate prediction of the battery remaining service time. Two identical 3.6-V/16.5-Ah Li-ion battery cells were repeatedly cycled with constant current and dynamic stress test current profiles at room temperature, and their discharge capacities were recorded. The proposed technique shows that very accurate SOC estimation results can be obtained provided enough training data are used to train the ANN models. Model derivation and experimental verification are presented in this paper. [ABSTRACT FROM AUTHOR]

Currently available wireless charging technology for portable electronics demonstrates several shortcomings. For the consumers, the two major shortcomings are limited receiver positioning flexibility and lower efficiency compared to hard-connected charging. For the industry, the major disadvantages are higher cost and complexity in design and control. To overcome these shortcomings and disadvantages, this paper presents a novel control method for unity-gain frequency tracking (UGFT) under coupling coefficient $(k)$ variation in a resonant converter containing a symmetrically implemented series–series (SS) resonant tank. An SS resonant converter employing the UGFT control provides several desirable features: the need for digital communication between the transmitter and the receiver to achieve leakage inductance compensation is eliminated, the design is robust against coupling (k)$ and load (Q)$ variations, the SS resonant converter can operate most of the time at the frequency of highest efficiency (unity-gain frequency ), and the downstream regulator commonly employed in a wireless charging system may be eliminated. Furthermore, in this paper, frequency-domain characteristics of SS resonant tank are explained in detail to illustrate various desirable characteristics. Detailed design criteria for SS resonant tanks are provided to achieve these characteristics. Throughout the analysis, various simulation results are provided to complement the discussion. The proposed UGFT control method is validated through experimental results. [ABSTRACT FROM AUTHOR]

Reusing electric vehicle batteries once retired from the automotive application is stated as one of the possible solutions to reduce electric vehicle costs. Many publications in the literature have analyzed the economic viability of such a solution, and some car manufacturers have recently started running several projects to demonstrate the technical viability of the so-called battery second life. Nevertheless, the degradation behavior of second life batteries remains unknown and represents one of the biggest gaps in the literature. This paper aims at evaluating the effects of lithium-ion nickel manganese cobalt/carbon (NMC/C) battery state of health (SOH) and ageing history over the second life performance on two different applications, a residential demand management application and a power smoothing renewable integration application. The performance and degradation of second life batteries were assessed both at the cell level and at stack level. Homogeneous and heterogeneous stacks were analyzed in order to evaluate the impact of cell-to-cell history and SOH differences over the battery performance and degradation behavior. Results obtained showed a strong influence of the first life battery ageing history upon the second life battery performance and degradation. Thereby, proper monitoring and battery selection appears crucial to certify the technical viability of battery second life. [ABSTRACT FROM PUBLISHER]

This paper deals with the arc flash hazard calculation in large energy storage systems (ESSs), with specific reference to battery energy storage systems (BESSs) and supercapacitor energy storage systems (SESSs). Due to the lack of international harmonized standards and the growing use of large ESSs, the evaluation of arc flash hazard associated with BESS maintenance operation is an interesting subject. In this study, battery circuit models, based on experimental short-circuit tests carried out by TERNA (the Italian transmission system operator) and a simplified supercapacitor circuit model, both coupled with a nonlinear arc resistance model, are used to assess the incident energy related to arc flash in BESSs and SESSs, respectively. Efficient and cost-effective solutions, able to reduce incident energy below the safe value 8 cal/cm2 and based on the installation of fast-acting fuses, are then proposed and discussed. [ABSTRACT FROM PUBLISHER]

With the popularity of electrical vehicles, the lithium-ion battery industry is developing rapidly. To ensure battery safe usage and to reduce its average lifecycle cost, accurate state of charge (SOC) tracking algorithms for real-time implementation are required for different applications. Many SOC estimation methods have been proposed in the literature. However, only a few of them consider the real-time applicability. This paper classifies the recently proposed online SOC estimation methods into five categories. Their principal features are illustrated, and the main pros and cons are provided. The SOC estimation methods are compared and discussed in terms of accuracy, robustness, and computation burden. Afterward, as the most popular type of model-based SOC estimation algorithms, seven nonlinear filters existing in literature are compared in terms of their accuracy and execution time as a reference for online implementation. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries are regarded as the key energy storage technology for both e-mobility and stationary renewable energy storage applications. Nevertheless, Lithium-ion batteries are complex energy storage devices, which are characterized by a complex degradation behavior, which affects both their capacity and internal resistance. This paper investigates, based on extended laboratory calendar ageing tests, the degradation of the internal resistance of a lithium-ion battery. The dependence of the internal resistance increase on the temperature and state-of-charge level has been extensive studied and quantified. Based on the obtained laboratory results, an accurate semiempirical lifetime model, which is able to predict with high accuracy the internal resistance increase of the lithium-ion battery over a wide temperature range and for all state-of-charge levels, was proposed and validated. [ABSTRACT FROM AUTHOR]

The lithium-ion batteries are commonly used in electric vehicle (EV) applications due to their better performances as compared with other batteries. However, lithium-ion battery has some drawbacks such as the overcharged cell which has a risk of explosion, the undercharged cell eventually reduces the life cycle of the battery, and unbalanced charge in series battery gradually reduces overall charge capacity. This paper presents a battery charge equalization algorithm for lithium-ion battery in EV applications to enhance the battery's performance, life cycle, and safety. The algorithm is implemented in series-connected battery cells of 15.5 Ah and 3.7 V nominal each using a battery monitoring integrated circuit for monitoring and equalization of an 8-cell battery pack using a bidirectional flyback dc–dc converter as the channel for charging and discharging of the battery cell. The obtained results show that the developed charge equalization controller algorithm performs well in equalizing both undercharged and overcharged cells, and equalizes the cell within the safety operation range of 3.81 V. To validate the charge equalizer performance, the proposed algorithm outperforms with other studies in terms of balancing, equalization speed, low power loss, and efficiency. Thus, the proposed battery charge equalization algorithm proves an effective and automated system to modularize the battery charge that improves the safety and life cycle of battery. [ABSTRACT FROM PUBLISHER]

Energy storage systems based on Lithium-ion (Li-ion) batteries have been proposed as an environmentally friendly alternative to traditional conventional generating units for providing grid frequency regulation. One major challenge regarding the use of Lithium-ion batteries in such applications is their higher cost—in comparison with other storage technologies or with the traditional frequency regulation methods&#x2014.combined with performance-degradation uncertainties. In order to surpass this challenge and to allow for optimal sizing and proper operation of the battery, accurate knowledge about the lifetime of the Li-ion battery and its degradation behavior is required. Thus, this paper aims to investigate, based on a laboratory developed lifetime model, the degradation behavior of the performance parameters (i.e., capacity and power capability) of a Li-ion battery cell when it is subjected to a field measured mission profile, which is characteristic for the primary frequency regulation service. [ABSTRACT FROM AUTHOR]

In this paper, a novel battery electric vehicle (BEV) concept based on a small fixed and a big swappable Li-ion battery pack is proposed in order to achieve longer range, lower initial purchase priceand lower energy consumption at short ranges. For short ranges, the BEV is only powered by the relatively small-fixed battery pack, without the large swappable battery pack. In this way, the mass of the vehicle is reduced and, therefore, the energy consumed per unit distance is improved. For higher ranges, the BEV is powered by both battery packs. This concept allows the introduction of subscription-based ownership models to distribute the cost of the large battery pack over the vehicle lifetime. A methodology is proposed for the analysis and evaluation of the proposed concept in comparison with a direct owned nonswappable single-pack BEV, proving that significant improvements on city fuel economy (up to 14%) and economic benefits are achievable under several scenarios. These results encourage further study of battery swapping service plans and energy management strategies. [ABSTRACT FROM AUTHOR]

Due to the inconsistent and varied characteristics of lithium-ion battery (LiB) cells, battery pack modeling remains a challenging problem. To model the operation of each cell in the battery pack, considerable work effort and computation time are needed. This paper proposes a data-driven bias-correction-based LiB modeling method, which can significantly reduce the computation work and remain good model accuracy. [ABSTRACT FROM AUTHOR]

This paper presents an energy management approach for a hybrid energy system comprised of a photovoltaic (PV) array and a polymer electrolyte membrane fuel cell (PEMFC). A single storage device, i.e., a Li-ion battery module, is used in the proposed structure. Linear proportional-integral (PI) and nonlinear flatness-based controllers for dc bus stabilization for power plants are compared. To verify the control approaches, a hardware system is realized with analog circuits for the PV, FC, and battery current control loops (inner controller loops) and with numerical calculation (dSPACE) for the external energy control loops. Experimental results with small-scale devices [namely, a PV array (800 W, 31 A), a PEMFC (1200 W, 46 A), and a Li-ion battery module (11.6 Ah, 24 V)] illustrate the excellent energy management scheme during load cycles, and the nonlinear differential flatness-based control was determined to provide improved dc bus regulation relative to a classical linear PI control method. [ABSTRACT FROM PUBLISHER]

This paper studies the characteristics of battery packs with parallel-connected lithium-ion battery (LiB) cells. To investigate the influence of the cell inconsistency problem in parallel-connected cells, a group of different degraded LiB cells were selected to build various battery packs and test them using a battery test bench. The physical model was developed to simulate the operation of the parallel-connected packs. The experimental results and simulation indicate that, with different degraded cells in parallel, there could be capacity loss and large difference in discharge current, which may cause further accelerated degradation and a more serious inconsistency problem. [ABSTRACT FROM PUBLISHER]

In the last few years, several Li-ion battery technologies have been studied and developed for their use in electric vehicles (EVs). Among them, lithium iron phosphate (LFP) batteries are considered a promising battery technology for EVs, due to their key advantages, such as cycle life, efficiency, and reliability, to name a few. This paper evaluates several commercial LFP batteries, studied under various testing scenarios, including cycle life, energy efficiency, power capability, or internal resistance test. The obtained results are compared with the long-term U.S. Advanced Consortium (USABC) goals, in order to validate the feasibility of this technology for its use in EVs. We found that although the tested LFP batteries successfully met some important USABC goals, there are still several technical challenges to be addressed, such as the increase of the energy density or the reduction of the final cost. [ABSTRACT FROM PUBLISHER]

The development of lifetime estimation models for Lithium-ion battery cells, which are working under highly variable mission profiles characteristic for wind power plant applications, requires a lot of expenditures and time resources. Therefore, batteries have to be tested under accelerated lifetime aging conditions. This paper presents a three-stage methodology used for accelerated lifetime testing of Lithium-ion batteries. The results obtained at the end of the accelerated aging process were used for the parameterization of a performance-degradation lifetime model, which is able to predict both the capacity fade and the power capability decrease of the selected Lithium-ion battery cells. In the proposed methodology both calendar and cycling lifetime tests were considered since both components are influencing the lifetime of Lithium-ion batteries. Furthermore, the proposed methodology was validated by running a verification stage of the lifetime model, where Lithium-ion battery cells were tested at normal operating conditions using an application specific mission profile. [ABSTRACT FROM AUTHOR]

In this paper, a method to estimate the capacity of individual lithium ion battery cells during operation is presented. When having two different states of charge of a battery cell as well as the transferred charge between these two states, the capacity of the battery cell can be estimated. The method is described in detail and validated on a battery cell with a current pulse test cycle. It is then applied to a real-life cycle; the accuracy is analyzed and discussed. [ABSTRACT FROM AUTHOR]