Battery Power System Research Articles

Hydrogen energy storage integrated battery and supercapacitor based hybrid power system: A statistical analysis towards future research directions

Environmentally friendly and pollution-free hydrogen cell, battery and supercapacitor hybrid power system has taken the attention of scientists in recent years. Several notable advancements in energy storage mechanisms with hybrid power systems have been made during the last decade, influencing innovation, research, and the possible direction for improving energy storage technologies. This paper represents a quantitative analysis of all knowledge carriers with mathematical and statistical methods of hydrogen energy storage to establish a hybrid power system. For selecting the top cited papers in this topic, related articles on energy storage mechanisms for hybrid power systems were searched in the Scopus database under specified predetermined parameters. The selection technique of the most cited paper was based on filtered keywords in the hybrid hydrogen energy storage-based hybrid power system and related research during 2008–2021. About 48% of all articles have been published between 2016 and 2019; 21% will have originated from China; and 29% of the papers have used batteries as a form of energy storage in the application of electric vehicles. Most of the articles contain experimental work (25.11%) followed by simulation analysis (25%) and systematic and nonsystematic review (18.75%). Related publications with the most citations were published in 35 different impactful journals from different publishers and nations. This research found that integrating hydrogen energy storage with battery and supercapacitor to establish a hybrid power system has provided valuable insights into the field's progress and development. Moreover, it is a thriving and expanding subject of study. Bibliometric analysis was used to identify the most significant research publications on the subject of hybrid energy storage, mapping the multidisciplinary character, illustrating nature and trends, and outlining areas for further research. The process of collecting, selecting, and analyzing the most cited articles is expected to contribute to a methodical foundation for future developments of hydrogen energy storage systems and provide viable research paths toward attaining a hybrid power system.

Modeling and simulation of pure electric vehicle composite power supply

In order to solve the problem of high discharge current, serious heating and low service life of pure electric vehicle with single power battery system driving at high power. Design a top-level model of the composite power supply with battery and ultra-capacitor for pure electric vehicles in the simulation software ADVISOR, propose an energy management control strategy based on logic threshold control theory. Based on MATLAB/Simulink environment, set up a logic threshold limit filtering power shunt module and chose the working condition of NEDC for simulation. The results show that, compared to single battery system, a composite power system embedded in the logic threshold control strategy of filtering thought can distributes the power between the battery and the ultra-capacitor more reasonably, effectively improves the peak output power of the battery, avoiding high current charge and discharge of batteries, extends the life of the battery, and improve the vehicle's power and economy.

Energy-efficient scheduling for an energy-intensive industry under punitive electricity price

As global warming and climate change become more and more serious, governments and scholars are paying more and more attention to these problems. Considering that consumption in manufacturing accounts for about one-half of the world's total energy consumption, the industrial sector is extremely important for preventing global warming. Facing with a multi-objective scheduling problem in the energy-intensive industries under punitive electricity price, a hybrid flow shop scheduling problem with onsite PV power generation and battery system is proposed. An improved multi-objective evolutionary algorithm based on decomposition is adopted, which integrates the low-carbon method with existing algorithms in three stages. First, an enhanced NEH heuristic algorithm is used to improve the quantity of initial solution in the initialization. Then the right-shift and speed scaling method are adapted to reduce the total energy consumption without affecting the maximum completion time. In the third stage, the distribution of renewable energy is performed, and the renewable energy is rescheduled based on the electricity range. The result of random instances and critical peak pricing verify the effectiveness of the proposed study.

Reliability Analysis of the High-Voltage Power Battery System Based on the Polymorphic Fuzzy Fault Tree

Accidents caused by the failure of high-voltage power battery systems are rising with the increase of pure electric commercial vehicles. The fault tree analysis method based on traditional reliability is no longer suitable for quantitative evaluation of polymorphic systems. In this paper, the polymorphic fuzzy fault tree of the high-voltage power battery system for pure electric commercial vehicles is established and analyzed qualitatively and quantitatively based on a combined theory of the polymorphic theory, fuzzy mathematical theory, group decision theory, and fault tree analysis theory. The results showed that the multistate reliability-analysis method of the fuzzy fault tree could describe the various fault states of the high-voltage power battery system. Through quantitative evaluation of the reliability of system, the low-temperature environment and CAN high and low reverse connection were the weakest links of the system, and the problem of the occurrence probability of each state of the unknown polymorphic bottom event in the sub-fault tree of the deteriorated-state mode was solved quickly using group decision-making to deal with fuzzy probability. It provides theoretical reference for system design and detection process, which has important practical significance for the improvement of high-voltage power battery system.

A Critical Review of Improved Deep Convolutional Neural Network for Multi-Timescale State Prediction of Lithium-Ion Batteries

Lithium-ion batteries are widely used as effective energy storage and have become the main component of power supply systems. Accurate battery state prediction is key to ensuring reliability and has significant guidance for optimizing the performance of battery power systems and replacement. Due to the complex and dynamic operations of lithium-ion batteries, the state parameters change with either the working condition or the aging process. The accuracy of online state prediction is difficult to improve, which is an urgent issue that needs to be solved to ensure a reliable and safe power supply. Currently, with the emergence of artificial intelligence (AI), battery state prediction methods based on data-driven methods have high precision and robustness to improve state prediction accuracy. The demanding characteristics of test time are reduced, and this has become the research focus in the related fields. Therefore, the convolutional neural network (CNN) was improved in the data modeling process to establish a deep convolutional neural network ensemble transfer learning (DCNN-ETL) method, which plays a significant role in battery state prediction. This paper reviews and compares several mathematical DCNN models. The key features are identified on the basis of the modeling capability for the state prediction. Then, the prediction methods are classified on the basis of the identified features. In the process of deep learning (DL) calculation, specific criteria for evaluating different modeling accuracy levels are defined. The identified features of the state prediction model are taken advantage of to give relevant conclusions and suggestions. The DCNN-ETL method is selected to realize the reliable state prediction of lithium-ion batteries.

IoT based Smart Battery Power and Wastage Level Tracking System for Solar Powered Waste Bin by GSM Technology

Solid waste collection and disposal are the primary issues in Oman as the country is lacking in effective management and suitable technologies. Rapid development in urban areas adds the fuel in these issues as it increases the risk of land pollution and health issues. The rotten vegetable wastes in the overfilled waste bins, spread the vector borne diseases in the surroundings. So, a proper management and monitoring system is needed to empty the waste bins in appropriate time. In this paper, Internet of Things (IoT) based smart system is proposed, to empty the waste bins in proper time. This system is designed in such a way that it is self-powered by photovoltaic panel which is embedded on the top of the waste bin lid. An ultrasonic sensor is used to sense the filling level of wastes and energy sensor module is used to sense the voltage and power of the battery unit. A microcontroller is used to estimate the filling level of wastes and also used to measure the voltage and power of the battery unit. Later, this information is transferred to the IoT server with the help of GSM (Global System for Mobile communication module). The experimental results show that the proposed system is very effective. The performance of the system is also validated by comparing its results with other existing systems.

An efficient hybrid photovoltaic battery power system based grid-connected applications

Power management systems for grid-tied photovoltaic-battery power systems are the focus of this research. Solar photovoltaic (PV) panels, lithium-ion batteries, and a voltage source inverter (VSC) are all part of the system. By employing the fuzzy logic (FL) technique, a PV system's power output can be maximized in a variety of weather circumstances. In addition, the state-of-charge-based power management system (PMS) was investigated to manage power sharing between sources and the grid and then manages the battery module's charge/discharge process. Active-reactive (PQ) control was used on the VSC converter while it was synced with the grid and regulated. In order to model and simulate the suggested system under various solar irradiances, Matlab/Simulink was employed. In contrast to the standard grid-connected inverter, which operates without batteries, the simulation results showed that adding the battery energy storage system BESS increased the system's performance. A grid-connected inverter that makes use of BESS can prevent the absence of PV energy or shading of the arrays. To explain why PMS is so effective, the simulations show that the injected grid current is more stable and has less total harmonic distortion (THD).

Lithium-Ion Battery Model Parameters Estimation Using Equivalent Circuit Model for E-mobility Applications

Accurate estimation of battery internal model parameters and consequently SOC prediction is crucial in any battery power system. Hence, it is a fundamental need in electric vehicles, smart grids, and energy storage systems. The accuracy of parameters identification will affect the battery management system, battery safety, characteristics, and performance, which mainly depends on battery model parameters. So, to estimate the parameters accurately and easily, we require effective, simple, and robust parameters estimation algorithms. In this article, we propose a new method for estimation of parameters using least square method algorithm for Lithium-Ion Batteries (LIBs) for Electric Vehicle (EV) applications. In this, a second-order RC equivalent circuit model is considered for estimation of parameters of NMC battery. The estimation of parameters and relation between OCV-SOC nonlinear is obtained from the experimental data. This proposed method shows that the calculation of parameters is fast and efficient.

Layout of the elements of the accumulator fuel supply system on a diesel engine

A structural scheme of the battery power supply system and the placement of its elements on a promising "16ЧН26/28" diesel locomotive is developed. The layout of the fuel supply system was made using solid modeling, taking into account the analysis of existing schemes of battery power systems. Keywords: diesel generator, battery fuel supply system, camshaft drive, block fuel pump, batteries, efficiency, environmental friendliness. mab5-5@yandex.ru, andrew_warsaw@mail.ru

Efficient Flatness Based Energy Management Strategy for Hybrid Supercapacitor/Lithium-ion Battery Power System

This article offers a flatness theory-based energy management strategy (FEMS) for a hybrid power system consisting of a supercapacitor (SC) and lithium-ion battery. The proposed FEMS intends to allocate the power reference for the DC/DC converters of both the battery and SC while attaining higher efficiency and stable DC bus voltage. First, the entire system model is analyzed theoretically under the differential flatness approach to reduce the model order as a flat system. Second, the proposed FEMS is validated under different load conditions using MATLAB/Simulink. Thus, this FEMS provides high-quality energy to the load and reduces the fluctuations in the bus voltage. Moreover, the performance of the FEMS is compared with the load following (LF) strategy. The obtained results show that the proposed FEMS meet the real load power under fast variations with good power quality compared to the classical LF strategy, where the maximum overshoot of the bus voltage is 5%.

Deploying battery technology for marine vessel electrification

The application of battery power systems has increased in the marine and offshore industry. Most uses are targeted toward reducing the fuel consumption or wholly electrifying the surface vessel. The types of ships that used battery power systems are reviewed, and the design and challenges of using lithium-ion batteries are discussed. The trend of customizing the battery power system in containerized form is explored in this article. The use of a lithium battery onboard the vessel needs to follow certain standards from an international accredited classification society, such as the American Bureau of Shipping (ABS), which are briefly discussed.

Complex dual-tree wavelet transform and unified power management based control architecture for hybrid wind power system

This study proposes a complex dual-tree wavelet transform (CDTWT) based control technique for a combined sensitive load, battery, and hybrid wind power system (HWPS) to improve the power quality (PQ). To make the system hybrid both DC-grid and AC-grid are connected through two parallel inverters and to circumvent the sudden power demand, it is connected to the main grid. The CDTWT based control technique easily decomposes the non-linear load current into different frequency levels and extracts the fundamental line frequency component for the computation of the actual active current component. In addition to that, to improve the power reliability (PR) and generate the desired current signals, a novel centralized control and power management (CCPM) approach is proposed. The generated reference current is used to coordinate both of the parallel inverters for offering synchronize power flow, regulate the voltage and frequency and offer regardless of switching operation, at both grid supporting and islanding conditions. The MATLAB/Simulink software is used to develop and test the proposed HWPS at different working modes as the failure of one inverter and the sudden addition of two wind turbines at grid-supporting mode and to show battery functionalities at islanding modes of operation. To justify the necessity of the proposed controller, the total harmonic distortion (THD), stability, and advancement of CDTWT results are also presented at different operating modes. From the test results, it is found that with the presence of 20.06% non-linear load current, the overall improvement percentage of inverter and grid current is 96%-97% and 99% respectively. In addition to that, the proposed technique takes only 0.04 s-0.05 s transition time. The above percentages are well within the prescribed limit of IEEE-1541 and IEEE 1547–2018 and are suggested for real-time complex microgrid operation.

On-Line Estimation Method of Lithium-Ion Battery Health Status Based on PSO-SVM

Battery management system (BMS) refers to a critical electronic control unit in the power battery system of electric vehicles. It is capable of detecting and estimating battery status online, especially estimating state of charge (SOC) and state of health (SOH) accurately. Safe driving and battery life optimization are of high significance. As indicated from recent literature reports, most relevant studies on battery health estimation are offline estimation, and several problems emerged (e.g., long time-consuming, considerable calculation and unable to estimate online). Given this, the present study proposes an online estimation method of lithium-ion health based on particle swarm support vector machine algorithm. By exploiting the data of National Aeronautics and Space Administration (NASA) battery samples, this study explores the changing law of battery state of charge under different battery health. In addition, particle swarm algorithm is adopted to optimize the kernel function of the support vector machine for the joint estimation of battery SOC and SOH. As indicated from the tests (e.g., Dynamic Stress Test), it exhibits good adaptability and feasibility. This study also provides a certain reference for the application of BMS system in electric vehicle battery online detection and state estimation.

A multi-star synchronous machine model for real-time digital simulation and its applications

Poly-phase electric machines have the advantages of low ripple in torque, better fault tolerance and high reliability in operation. Such properties make them attractive for applications in renewable energies, electric ship propulsion, traction, aircraft systems and electric vehicles [1,2]. Failure of the drive system through a few phases could be tolerated by operating the remaining phases of the machine. One popular group amongst poly-phase electric machines is the category of multi-star machines.This paper presents development and validation of a multi-star synchronous machine model for a real-time digital simulator. The paper starts with the introduction and analysis of multi-star machines. A generalized method of Vector-Space Decomposition (VSD) is introduced for analyzing machines with an arbitrary number of stars. The method of incorporating the model into the network solution of real-time electromagnetic transient program is described. For the purpose of demonstration, a typical circuit of a marine electric vessel, containing poly-phase generators, power electronic converters, DC bus, hotel load, battery, and poly-phase propulsion systems is simulated in real time.

Adaptive robust co-optimization of wind energy generation, electric vehicle batteries and flexible AC transmission system devices

The ever-increasing penetration of wind energy generation (WEG) and electric vehicle (EV) batteries in power systems could bring two significant challenges to day-ahead energy balancing markets. First challenge, the uncertainty of WEG and random behavior of the EV batteries can raise energy imbalance in energy markets. Second challenge, the intermittent nature of WEG and uncontrolled EV batteries charging, bring high congestion costs and new congestion patterns in transmission system. In this condition, there is no guarantee that the WEG is deliverable throughout the power system. The hourly coordination of WEG units with EV batteries can play important roles in addressing the first challenge. Similarly, to addressing the second challenge, a transmission impedance adjustment (TIA) device is taken as a promising way to reduce transmission congestion and promote the integration of large-scale WEG and EV batteries through controlling the power flows. However, utilization of TIA device is limited nowadays due to the complexity of this device in the optimization problem of day-ahead energy market clearing with the DC approximation of the power flow network. Consequently, a computationally efficient methodology, which is compatible with existing customary solvers, is proposed to adjust the TIA device set point with minimal modification efforts. An adaptive robust optimization formulation is adapted in the proposed problem to handle the WEG uncertainty. Finally, the simulation results on six and IEEE 118 bus test systems suggest that: 1) substantial economic savings can be achieved through utilization of WEG and storage capability of EV batteries, beyond the independent capabilities of TIA technology; 2) the TIA device plays a critical role in removing transmission congestion; and 3) the storage capability of EV batteries could relieve the uncertainty of WEG and increase its dispatchability.

Analysis, control, and modeling of the three‐port converter without port voltage constraint for photovoltaic/battery system application

AbstractFor a photovoltaic (PV)/battery power system consisting of PV module, energy storage system, and local load, using a three‐port converter (TPC) instead of several single‐input converters is more desirable, such as simpler circuit, higher efficiency, lower cost, and centralized control without communication circuit. In this paper, a TPC is proposed and analyzed, which includes operating modes, steady‐state performance, and parameter design. Compared with other converters, the proposed TPC has a low cost, compact structure, and a more flexible voltage relationship among all ports. Moreover, energy management and control methods are further proposed for PV/battery systems based on the proposed converter, which can achieve maximum power point tracking (MPPT) of PV module and constant output voltage. In order to design the control loop and realize multivariable optimal control, a small‐signal model of the converter is obtained in each operation mode. Then a detailed decoupling design approach based on a small‐signal model is provided to allow a separate controller design for the proposed converter. Finally, the validity of the proposed converter and its energy management and control method are verified by experimental results.

Metal-organic frameworks enable broad strategies for lithium-sulfur batteries.

The lithium-sulfur (Li-S) battery is considered to be a potential next-generation power battery system, however, it is urgent that suitable materials are found in order to solve a series of challenges, such as the shuttle effect and lithium dendrite growth. As a multifunctional porous material, metal-organic frameworks (MOFs) can be used in different parts of Li-S batteries. In recent years, the application of MOFs in Li-S batteries has been developed rapidly. This review summarizes the milestone works and recent advances of MOFs in various aspects of Li-S batteries, including cathode, separator and electrolyte. The factors affecting the performance of MOFs and the working mechanisms of MOFs in these different parts are also discussed in detail. Finally, the opportunities and challenges for the application of MOFs in Li-S batteries are proposed. We also put forward feasible solutions to related problems. This review will provide better guidance for the rational design of novel MOF-based materials for Li-S batteries.

RETRACTED ARTICLE: Enhancement of network lifetime by fuzzy based secure CH clustered routing protocol for mobile wireless sensor network

Mobile Wireless sensor network conveys an innovative archetype of real time systems by means of restricted computation, transmission, storage, and vigor resources utilized for massive range of appliances wherever traditional system is frequently infeasible. Sensor nodes are compactly organized in an aggressive atmosphere to observe, identify, and scrutinize physical occurrence and utilized significant quantity of energy during broadcasting information. It is unfeasible and occasionally impractical to change battery and to preserve wider network lifetime. So, duration of battery and energy preservation is an exigent complication. Exact ClusterHead determination is one of the concerns that can condense energy utilization considerably. Low-energy adaptive-clustering hierarchy (LEACH) is most prominent hierarchical routing technique, ClusterHead is nominated in alternation basis related on probabilistic threshold cost and CHs are permitted to transfer events to basestation. In proposed FCHIDS tactic, a Outstanding-ClusterHead is nominated among CHs in cluster that can transfer information to mobile basestation by deciding appropriate fuzzy factors outstanding battery power, basestation mobility, clusters centrality and intrusion detection system. Fuzzy assumption engine is utilized to decide Outstanding-ClusterHead. The consequences are from simulating NS-2 and illustrations shows that proposed FCHIDS tactic achieves upto 5% superior than LEACH technique in provisions with partial amount of nodes active, enhanced constancy, and improved lifetime. Consequently it achieves upto 5% reduction in initial node expires from network than LEACH technique.

Research on energy management and control method of microgrid considering health status of batteries in echelon utilization

With the large-scale application of electric vehicles, the use of retired power batteries in power system and other fields has become a trend in the future. How to quickly and accurately estimate the health status of power batteries and reasonably carry out energy management has become one of the main problems to be solved. This paper takes the application of retired power batteries in microgrid (MG) as an example. Firstly, considering the influence of the depth and times of batteries charge and discharge on the operation life, the life loss model of retired power batteries is established, and the coupling relationship between the power batteries life decay model and SOC, SOH is established. Secondly, according to the characteristics of SOC and SOH, K-means clustering method is used to cluster the batteries to construct the energy storage system (ESS). Finally, considering the characteristics of supply and demand balance, operation reliability and economy, the energy management and control of ESS in MG is carried out. Simulation results show that the proposed energy management and control method can effectively improve the economy, reliability and security of the ESS in the process of echelon utilization.

Optimal Design of Wind/PV/Diesel/Battery Power System for telecommunication application in a remote Algeria

Algeria has embarked on an ambitious renewable energy program in order to increase total food production. It has a large number of remote small villages and islands that lack in the electricity, and probability of connecting them with the high voltage gridlines in the near future is very poor due to financial and technical constraints. This paper proposes the use of a PV, wind and diesel generator hybrid system with storage element in order to determine the optimal configuration of renewable energy in ALGERIA. The principals’ interests of this system are the independence production, and the supplying of electric energy in isolated localities. Have at one’s the energetic and economic models, and simulation tools, we effected an optimization study based on mixed productions. For this approach, the energetic resources of sites where are implanted telecommunications systems and their consumption are supposed known. Then the problem is the optimization of electric generators using these resources, enable to have an optimal type system for the powering of telecommunications equipments in rural site of Algeria. Homer (hybrid optimization model for electric renewable) simulation software was used to determine the technical feasibility of the system and to perform the economical analysis of the system.