An adaptive Kalman filtering based State of Charge combined estimator for electric vehicle battery pack

Ah counting is not a satisfactory method for the estimation of the State of Charge (SOC) of a battery, as the initial SOC and coulombic efficiency are difficult to measure. To address this issue, a new SOC estimation method, denoted as “AEKFAh”, is proposed. This method uses the adaptive Kalman filtering method which can avoid filtering divergence resulting from uncertainty to correct for the initial value used in the Ah counting method. A Ni/MH battery test procedure, consisting of 8.08 continuous Federal Urban Driving Schedule (FUDS) cycles, is carried out to verify the method. The SOC estimation error is 2.4% when compared with the real SOC obtained from a discharge test. This compares favorably with an estimation error of 11.4% when using Ah counting.     

Subspace‐based modeling and parameter identification of lithium‐ion batteries

For reliable and safe operation of lithium‐ion batteries in electric vehicles, the monitoring of state‐of‐charge and state‐of‐health is necessary. However, these internal states cannot be measured directly, which are usually estimated through model‐based techniques. Therefore, an accurate application‐oriented battery model is of significant importance. The purpose of this paper is to present a novel method on battery modeling and parameter identification. In this work, a state‐space model with clear mathematical and electrochemical meanings is proposed on the basis of the electrochemical basics of lithium‐ion batteries. The frequency‐domain characteristics of the lithium‐ion batteries are also investigated. On the basis of the frequency analysis, an identification test profile that can excite the dynamic characteristics of the battery fully and persistently is proposed. A subspace‐based algorithm is then adopted to identify the parameters of the battery model. The performance and robustness of the estimated model are validated through some experiments and simulations. The validation results show that the proposed method can achieve an acceptable accuracy with the maximum error being less than 2%. Copyright © 2013 John Wiley & Sons, Ltd.     

Synthesis of nitrogen‐doped graphene catalyst by high‐energy wet ball milling for electrochemical systems

Platinum group metal‐based (PGM) catalysts are widely applied in many electrochemical systems such as fuel cells or metal–air batteries because of their excellent catalytic performance. But the high raw material cost of PGM catalysts has become a significant issue. In recent years, huge efforts have been made to reduce the material cost of electrochemical systems by developing non‐PGM catalysts, and as one of the promising non‐PGM catalysts, nitrogen‐doped graphene (N‐G) has emerged. In this research, nanoscale high‐energy wet ball milling methodology was investigated as an effective synthesis method for N‐G catalysts by using graphene oxide and melamine as raw materials. The main purpose is to study reaction mechanism of the synthesis process and the physical, chemical, and electrochemical properties of N‐G catalysts generated by this mechanochemical approach. The elemental composition, chemical bonding composition, and electron transfer number of the synthesized products were characterized. The results show that the electron transfer number of the N‐G catalyst with 23.2 at% nitrogen doping content, synthesized by the high‐energy wet ball milling method, has attained a value of 3.87, which is close to the number (3.95) of Pt/C catalysts, and the grinding time was found to be a significant factor in the properties of N‐G catalysts in the experiments. The results also show that the high‐energy wet ball milling developed in this research is a promising method to synthesize high‐performance N‐G catalysts with a simple and easy controllable approach. Copyright © 2016 John Wiley & Sons, Ltd.     

Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries

The coulomb counting method is expedient for state-of-charge (SOC) estimation of lithium-ion batteries with high charging and discharging efficiencies. The charging and discharging characteristics are investigated and reveal that the coulomb counting method is convenient and accurate for estimating the SOC of lithium-ion batteries. A smart estimation method based on coulomb counting is proposed to improve the estimation accuracy. The corrections are made by considering the charging and operating efficiencies. Furthermore, the state-of-health (SOH) is evaluated by the maximum releasable capacity. Through the experiments that emulate practical operations, the SOC estimation method is verified to demonstrate the effectiveness and accuracy.     

Multi‐fault synergistic diagnosis of battery systems based on the modified multi‐scale entropy

Faults of lithium batteries in their early stage in electric vehicles (EVs) are usually undetectable, and their characteristics are difficult to be extracted by conventional methods. This paper presents a novel synergistic diagnosis scheme for multiple battery faults using the modified multi‐scale entropy (MMSE). The proposed MMSE can effectively extract the multi‐scale features of complex battery signals in the early stages of battery faults as well as overcome the shortage of the coarse‐grained mode in the standard multi‐scale entropy. The simulation results on experimental data and the real‐world operational vehicles show that the proposed method can effectively detect and locate multiple battery faults/abnormities before they trigger the alarm thresholds. The defined sensitivity factor can implement real‐time evaluation on abnormities with high efficiency and stability, and the developed variable‐calculation‐window diagnosis scheme can synchronously detect and locate different fault types in real time. Furthermore, feasibility, stability, reliability, versatility, robustness, and practicality of the proposed method are separately verified using multiple sets of real‐world operation data. More importantly, the proposed method also provides feasibility to effectively prevent battery thermal runaway caused by multiple battery abnormities/faults. The applications of multi‐scale entropy theory is the first of its kind to battery fault diagnosis on the real‐world operational vehicles.     

Introducing the energy efficiency map of lithium‐ion batteries

The charge, discharge, and total energy efficiencies of lithium‐ion batteries (LIBs) are formulated based on the irreversible heat generated in LIBs, and the basics of the energy efficiency map of these batteries are established. This map consists of several constant energy efficiency curves in a graph, where the x‐axis is the battery capacity and the y‐axis is the battery charge/discharge rate (C‐rate). In order to introduce the energy efficiency map, the efficiency maps of typical LIB families with graphite/LiCoO₂, graphite/LiFePO₄, and graphite/LiMn₂O₄ anode/cathode are generated and illustrated in this paper. The methods of usage and applications of the developed efficiency map are also described. To show the application of the efficiency map, the effects of fast charging, nominal capacity, and chemistry of typical LIB families on their energy efficiency are studied using the generated maps. It is shown how energy saving can be achieved via energy efficiency maps. Overall, the energy efficiency map is introduced as a useful tool for engineers and researchers to choose LIBs with higher energy efficiency for any targeted applications. The developed map can be also used by energy systems designers to obtain accurate efficiency of LIBs when they incorporate these batteries into their energy systems.     

Innovative multi‐processed N‐doped carbon and Fe3O4 cathode for enhanced bioelectro‐Fenton microbial fuel cell performance

A novel bioelectro‐Fenton microbial fuel cell (BEF‐MFC) cathode has been fabricated by modification of electrode using multi‐processing of nitrogen‐doped carbon (NDC)/nano‐Fe₃O₄ method with the aims of cost‐effectiveness, high oxygen reduction reaction (ORR) efficiency, and power performance enhancement. In this study, BEF‐MFC with carbon cloth (CC) cathode pyrolyzed with NDC‐M100/Fe₃O₄ at 700°C achieved higher ORR activity compared with the commercial Pt/C under same operational conditions. It also exhibited excellent crystalline structure according to high‐resolution transmission electron microscope (HRTEM) analysis. Moreover, using NDCN/Fe₃O₄ can facilitate further Fenton‐like reaction for the treatment of wastewater. Chemical oxygen demand (COD) removal efficiency of the reactor was 78% with maximum power density of 1.57 W/m³ in 216 hours. Thus, an innovative multi‐processing method with feasibility for enhanced wastewater treatment and improved power performance of the MFC was investigated. This can be effectively applied in related alternative energy production techniques and bio‐electrochemical systems in the future.     

A novel real‐time energy management strategy for plug‐in hybrid electric vehicles based on equivalence factor dynamic optimization method

The universal adaptive equivalent consumption minimization strategy (A‐ECMS) has the potential of being implemented in real‐time for plug‐in hybrid electric vehicles (PHEVs). However, the imprecise prediction of a long‐term future driving cycle and biggish computation burdens remain the barriers for further real vehicle application. Thus, it is of great significance to develop a real‐time optimal energy management strategy for PHEVs by weakening the influence of future driving cycle to the control accuracy and improving its computation efficiency. In this paper, a novel real‐time energy management strategy for PHEVs based on equivalence factor (EF) dynamic optimization method is proposed. Firstly, a novel proportional plus integral adaption law for calculating the dynamic optimal EF is established for A‐ECMS using only instantaneous information of current vehicle speed and battery state of charge. Second, three key coefficients are obtained and converted into a three‐dimensional look up tables, so as to determine the dynamic optimal EF. Finally, the method of fast searching the optimal engine torque is proposed, which significantly enhances the computational efficiency. Compared with A‐ECMS, the computational time of A‐ECMS2 is decreased near 94.8% and the deviation of fuel consumption is controlled within 4.4%. Both the numerical results and hardware‐in‐loop results prove that the proposed novel energy management strategy A‐ECMS2 has better real‐time performance and less computing burden than the general A‐ECMS.     

GGlueVaR‐based participation of electric vehicles in automatic demand response for two‐stage scheduling

Due to the uncertainty of the external situation and the varied ability of electric vehicle (EV) owners to understand and process information, the demand response optimization method is not timely and flexible enough. This article puts forward a two‐stage electric vehicle automatic demand response (ADR) optimization method based on generalized Glue value‐at‐risk (GGlueVaR) to solve existing problems. First, a two‐stage electric vehicle ADR optimization method is proposed considering both the EV owner ' s benefit and network load fluctuation. In the process of ADR, different risk preferences of electric vehicle owners affect the EV owner participation in ADR. Second, the GGlueVaR‐based EV owner willingness decision model is adopted to measure an EV group's risk attitude. Finally, a case study is provided to verify the effectiveness of the proposed method. Results show that the proposed model reduced the average charging cost of EV owners by 45% and increased the profit resulting from DR by 91% compared with the price‐based demand response model. Therefore, the proposed model is more efficient than disorder charging model. The method is timelier and more flexible compared with other prior demand response optimization methods.     

An effective and safe charging algorithm for lead‐acid batteries in PV systems

In this paper a new charging algorithm is proposed to charge lead‐acid batteries in photovoltaic (PV) systems. This algorithm can return discharged lead‐acid batteries to their 100% state of charge (SOC) quickly and at the same time can avoid the associated problems of the excessive gassing phenomenon at overcharge. The proposed algorithm can be applied in the PV systems by using a DC‐DC converter, which differs from the traditional on/off regulators in that it cannot only be used to charge the battery and protects it from overcharging, but it can also be used to quickly and safely charge the battery to 100% SOC through better exploitation of the available PV energy. The simulation results verify that, using the proposed algorithm, the discharged battery can always restore its 100% SOC compared with the conventional charging algorithms. Copyright © 2010 John Wiley & Sons, Ltd.     

Application of the variational iteration method to nonlinear non‐Fourier conduction heat transfer equation with variable coefficient

In this paper, a variational iteration method (VIM) has been applied to nonlinear non‐Fourier conduction heat transfer equation with variable specific heat coefficient. The concept of the variational iteration method is introduced briefly for applying this method for problem solving. The proposed iterative scheme finds the solution without any discretization, linearization, or restrictive assumptions. The results of VIM as an analytical solution are then compared with those derived from the established numerical solution obtained by the fourth order Runge–Kutta method in order to verify the accuracy of the proposed method. The results reveal that the VIM is very effective and convenient in predicting the solution of such problems, and it is predicted that VIM can find a wide application in new engineering problems. © 2011 Wiley Periodicals, Inc. Heat Trans Asian Res; Published online in Wiley Online Library ( wileyonlinelibrary.com/journal/htj ). DOI 10.1002/htj.20362     

Performance assessment of a passive core cooling design for cylindrical lithium‐ion batteries

Battery thermal management (BTM) system is an indispensable component for large‐sized lithium‐ion battery packs used in aerospace and automotive applications. Besides providing a proper temperature range for batteries to operate, thus improving their efficiency, lifespan, and safety, the BTM system also needs to be well designed with considering the cost, weight, and practicability. In this paper, an internal passive BTM system is proposed for the cylindrical Li‐ion batteries. The design embeds a phase change material (PCM) filled mandrel inside the battery to achieve the cooling effect. A thermal test cell is first fabricated and tested in a wind tunnel under different cooling scenarios, and it is also used to verify a numerical thermal model. The proposed BTM system is further examined through the model and found to be able to create a preferable environment for batteries to operate. Specifically, the core BTM system consumes less PCM and achieves lower temperature rises and more uniform temperature distributions than an external BTM system. The proposed design can also exert its full latent heat to manage the heat generated from the battery without having a thermally conductive matrix, which is usually composite with PCM in external BTM systems. In addition, experiments show that the battery equipped with the proposed BTM system is ready for intensive cycling tests.     

Graphene‐wrapped poly(2,5‐dihydroxy‐1,4‐benzoquinone‐3,6‐methylene) nanoflowers as low‐cost and high‐performance cathode materials for sodium‐ion batteries

Graphene‐wrapped poly 2,5‐dihydroxy‐1,4‐benzoquinone‐3,6‐methylene (PDBM) nanocomposites with three‐dimensional nanoflower structures have been successfully prepared through the ultrasonic exfoliation and reassembly process in methanol. Compact distribution of graphene into the nanocomposite has established a three‐dimensional conductive network, which contributes to improved properties on discharge capacity and cycle performance. Composite with 20 wt% graphene was proved the best ratio when used in sodium‐ion batteries. Its initial discharge capacity can achieve 210 at 30 mA g^?1. After 100 cycles, the capacity is stable at 121 mAh g^?1. The composite featuring highly conductive channels and multidimensional electron transport pathway is synthesized by an easy ultrasonic way, which may be applied in large scales for sodium‐ion batteries.     

Doubly fed induction generator‐based variable‐speed wind turbine: Proposal of a simplified model under a faulty grid with short‐duration faults

The aim of this study is to provide a simplified model of a variable‐speed wind turbine (VSWT) with the technology of a doubly fed induction generator (DFIG), which operates under faulty grid conditions. A simplified model is proposed, which consists of a set of electrical and mechanical equations that can be easily modeled as simplistic electrical circuits. It makes it an excellent tool to achieve fault ride‐through capability of grid‐connected VSWT with DFIGs. Both symmetrical and unsymmetrical grid faults, which cause symmetrical and unsymmetrical voltage sags, have been applied to the system in order to validate the model. The proposed simplified model has been compared with the traditional full‐order model under multiple sags (different durations and depths), and the results reveal that both models present similar accuracy. As the idea is to reduce the computational time required to simulate the machine behavior under faulty grid conditions, the proposed model becomes suitable for that purpose. The analytical study has been validated by simulations carried out with MATLAB .     

Comprehensive assessment of line‐/point‐focus combined scheme for concentrating solar power system

The line‐/point‐focus combined scheme for concentrating solar power (CSP) system is proposed. For solar field, the parabolic trough (PT) or linear Fresnel (LF) is used as the line‐focus preheating and evaporation stages while the solar tower is used as the point‐focus superheating and reheating stages. The combined schemes benefit from the high concentration ratio of point‐focus technology and low cost of line‐focus technology. Particularly, the combined scheme guarantees the concentrated solar thermal energy matching the temperature requirement of steam generation process with less exergy loss. Performance and economic assessments have been performed for 50 MW_e CSP system with two of the combined schemes, ie, PT (synthetic oil, SO) + Tower (molten salt, MS) and LF (direct steam generation, DSG) + Tower (DSG), as well as existing single schemes being the references, ie, PT (SO), LF (DSG), Tower (MS), and Tower (DSG). The comparative results show that the combined schemes are superior to liner‐focus schemes in efficiency and to point‐focus schemes in capital cost and scalability. Specifically, the PT (SO) + Tower (MS) system suggests the favorable potential in practical application with the highest annual net solar‐to‐electrical energy conversion efficiency of 16.07% and the reasonable levelized cost of electricity (LCOE) of 16.121 US cent/(kW·h). This work provides an alternative guidance for future development of the CSP technology.     

Degradation mechanisms in Li‐ion batteries: a state‐of‐the‐art review

One of the most prominent energy storage technologies which are under continuous development, especially for mobile applications, is the Li‐ion batteries due to their superior gravimetric and volumetric energy density. However, limited cycle life of Li‐ion batteries inhibits their extended use in stationary energy storage applications. To enable wider market penetration of Li‐ion batteries, detailed understanding of the degradation mechanisms is required. A typical Li‐ion battery comprised of an active material, binder, separator, current collector, and electrolyte, and the interaction between these components plays a critical role in successful operation of such batteries. Degradation of Li‐ion batteries can have both chemical and mechanical origins and manifests itself by capacity loss, power fading or both. Mechanical degradation mechanisms are associated with the volume changes and stress generated during repetitive intercalation of Li ions into the active material, whereas chemical degradation mechanisms are associated with the parasitic side reactions such as solid electrolyte interphase formation, electrolyte decomposition/reduction and active material dissolution. In this study, the main degradation mechanisms in Li‐ion batteries are reviewed. Copyright © 2017 John Wiley & Sons, Ltd.     

Multi‐phase method of estimation and adaptation of parameters of electrical battery models

Mathematical modeling of the battery lifetime is an important tool for the design of more efficient batteries, as well as for the optimization of their use. The electrical models class is among the classes of mathematical models used for this purpose, and a fundamental step to their application is the correct estimation of their parameters. This paper performs the mathematical modeling of Lithium‐Ion Polymer batteries lifetime through the electrical model of Tremblay, in which a multi‐phase method of estimation and adaptation of parameters is proposed, divided into three phases: discovery, learning, and inference. The multi‐phase method is based on two Artificial Intelligence techniques: genetic algorithms and artificial neural networks. The proposed method is validated by the simulation and experimental studies. From the results, it is concluded that the application of the multi‐phase method improves the effective accuracy of the Tremblay model, when it comes to adapt its parameters to the battery during runtime. For constant discharge currents, the average error reduction was 79%, when compared to the best set of parameters obtained by GA without the adaptation process. For variable current discharge curves, the method was able to reduce the error more than 35%. This method can be applied to other battery lifetime prediction models.     

Flow‐based electromagnetic‐type energy harvester using microplanar coil for IoT sensors application

Battery is the sole power source for Internet of thing (IoT) sensors. Due to limited shelf life, the batteries are required to be replaced intermittently. This periodic replacement of batteries is inflated in terms of both logistics and time. This article illustrates conceptual design, development, and characterization of a flow‐based electromagnetic‐type energy harvester (F‐EH) using microplanar coil for IoT sensors application. The F‐EH converts hydro energy into useful electrical energy utilizing electromagnetic transduction mechanism. The microfabrication and macrofabrication techniques adopted to manufacture harvester's components are presented. The F‐EH has been successfully characterized by laboratory scale experimental flow test loop commissioned for this work. Experimentation with associated uncertainty analysis prevails that at a matching impedance, the F‐EH can generate a 686 μW of maximum power at an operating flow rate of 12 L/min with an uncertainty of 8.1%.     

Comprehensive study of the performance of alkaline organic redox flow batteries as large‐scale energy storage systems

Alkaline‐based organic redox flow batteries (AORFBs) attract significant interest because they can retain the advantages of vanadium redox flow batteries (VRFBs) while being low‐cost because expensive vanadium is replaced with easily synthesizable metal‐free organic compounds and earth‐abundant raw materials. A comprehensive experimental study on the performance of AORFBs using alloxazine 7/8‐carboxylic acid (ACA) and ferrocyanide was conducted to investigate the feasibility of these batteries as large‐scale energy storage systems. The operating conditions, such as the electrolyte concentration, flowrate, and temperature, were varied in this study. The results show that the present AORFB achieves an energy efficiency above 76% at 80 mA cm^?2 at elevated temperature (55°C). Compared with those of VRFBs, AORFBs exhibit very good thermal stability and capacity retention. A large‐scale AORFB was constructed and tested to confirm the effectiveness of AORFBs.     

Initialization of DFIG wind turbines with a phasor‐based approach

The objective of this paper is to propose a simple approach to solve the steady state of a wind turbine (WT) equipped with a doubly fed induction generator (DFIG), which can be used to initialize dynamic studies of the machine. The idea is to model the rotor‐side converter (RSC) as a constant current source connected to the rotor of the DFIG. The resulting equivalent circuit consists of a voltage source in series with a reactance, which makes it possible to obtain simple phasor expressions that can be used to obtain the Park components of the variables. The proposed method is compared with the traditional Newton–Raphson algorithm, showing that it is easier and faster to implement, as it makes use of the phasor expressions and it does not require an iterative process to obtain the final solution. Finally, the results of the proposed method are used to simulate a 2‐MW DFIG‐based WT under three‐phase faults, considering three different WT‐operating points. In these simulations, the idea of constant rotor current is extrapolated to the entire event. The simulated results show that both current at torque peaks are reduced. The analytical study and the simulations have been carried out in Matlab ?.