Battery Balancing Research Articles

Active Battery Voltage Equalization Based on Chain-Loop Comparison Strategy

This paper describes active battery balancing based on a bidirectional buck converter, a flyback converter, and battery cells by using the proposed chain-loop comparison strategy. The role of the bidirectional buck converter is to charge/discharge the battery pack. During the charging period, the converter is in buck mode, and its output is controlled by constant current/voltage; during the discharging period, the converter is in boost mode, and its output is controlled by constant voltage. The role of the flyback converter is voltage equalization of the battery pack, and its output is controlled by constant current. A chain-loop comparison strategy is used to control battery voltage equalization. In this work, three equalization modes, namely, charging balance, discharging balance, and static balance, were considered. The voltage difference between the maximum and minimum is 0.007 V after a balancing time of 19.75 min, 0.005 V after a balancing time of 24 min, and 0.007 V after a balancing time of 20 min for charging balance, discharging balance, and static balance, respectively.

Switching Control for Voltage Balancing of Lithium Batteries

Abstract Battery system consists of many battery cells or modules with different characteristics, in order to achieve reliable, efficient and long time use of the battery system, and to avoid the performance difference between single cells due to manufacturing and aging, we need to balance the voltage of single cells. At present, the research and development progress of battery balancing technology lags far behind the development of battery technology. In order to achieve effective balancing of single cells in a battery pack, we propose a “switching tube + resistor” type passive balancing technology for single cell voltage, which is a method to distribute the switching time of the shunt circuit according to the voltage of each single cell, so as to control the charging current of single cells and achieve battery voltage balancing, but The traditional passive balancing method will make the battery management system unstable therefore it is difficult to put it into use, this paper proposes a new switching control algorithm to overcome the problem of passive balancing making the BMS unstable, thus providing an effective balancing method that can be used practically in the use of lithium batteries.

Research on the Human–Robot Collaborative Disassembly Line Balancing of Spent Lithium Batteries with a Human Factor Load

The disassembly of spent lithium batteries is a prerequisite for efficient product recycling, the first link in remanufacturing, and its operational form has gradually changed from traditional manual disassembly to robot-assisted human–robot cooperative disassembly. Robots exhibit robust load-bearing capacity and perform stable repetitive tasks, while humans possess subjective experiences and tacit knowledge. It makes the disassembly activity more adaptable and ergonomic. However, existing human–robot collaborative disassembly studies have neglected to account for time-varying human conditions, such as safety, cognitive behavior, workload, and human pose shifts. Firstly, in order to overcome the limitations of existing research, we propose a model for balancing human–robot collaborative disassembly lines that take into consideration the load factor related to human involvement. This entails the development of a multi-objective mathematical model aimed at minimizing both the cycle time of the disassembly line and its associated costs while also aiming to reduce the integrated smoothing exponent. Secondly, we propose a modified multi-objective fruit fly optimization algorithm. The proposed algorithm combines chaos theory and the global cooperation mechanism to improve the performance of the algorithm. We add Gaussian mutation and crowding distance to efficiently solve the discrete optimization problem. Finally, we demonstrate the effectiveness and sensitivity of the improved multi-objective fruit fly optimization algorithm by solving and analyzing an example of Mercedes battery pack disassembly.

A novel digital energy computation method for dynamic reconfigurable battery networks

Abstract Dynamic reconfigurable battery network (DRBN) is a promising method to overcome battery imbalance. As a complement, a battery management system (BMS) plays a key role in battery status estimation, battery topology reconfiguration, and thermal management. Different from the traditional BMS, a fully distributed DRBN control framework requires high efficiency and massive computation. Inspired by the computer architecture, we propose a novel digital energy computation method for DRBN. First, according to the first principle, we apply the idea of shielding terminal differences on the Internet to BESSs. Then, based on time-oriented management, the framework of DRBN is introduced to eliminate battery differences. Finally, a case analysis shows that DRBN can effectively realize battery balancing during the charging process.

Energy management and SoC balancing of distributed batteries in AC microgrids using consensus tracking control

This paper proposes a consensus tracking control method for energy management and state-of-charge (SoC) balancing of energy storage batteries in the grid-connected mode of AC microgrids. By adding a target power term to the consensus average control law, taking into account battery energy storage system (BESS) with various SoCs and various capacities, the stability and robustness of the proposed consensus control approach are analytically validated. Simulations of a state–space battery model and a detailed dynamic model of batteries in grid-connected mode are constructed in a Matlab environment. A detailed study of weighting matrices of the control approach is presented, and their suitable range is identified. The results show that the proposed method could effectively balance SoC for batteries of equal and different capacities, allowing the battery with the higher capacity to charge and discharge more than the others at the same time while still maintaining the target power. Furthermore, the controller successfully prevented deep discharge or overcharging of the batteries by disconnecting them when they reached their SoC limitations and compensating for this disconnection by raising their target power to maintain the same load.

Asynchronous deep reinforcement learning with gradient sharing for State of Charge balancing of multiple batteries in cyber–physical electric vehicles

This work targets the State of Charge (SoC) imbalance issue due to the mismatch across multiple batteries in cyber–physical electric vehicles (EVs) arisen from a variety of practical factors such as manufacturing tolerance, nonuniform aging process and uneven operation temperature. While most of existing SoC balancing approaches are model-based and require accurate prior knowledge, a data-driven asynchronous deep reinforcement learning (DRL) with gradient sharing is proposed to equilibrate the SoC of multiple battery packs in cyber–physical EVs under time-varying operating conditions, and the transmission of control signals in the EVs is formulated by ISO/IEC 15118 standards to ensure the security of the cyber–physical EVs. The gradient sharing (GS) based exploration scheme can expand the exploration space to diversify the actor policies in the training process and in turn reduce the entropy loss value and guarantee the convergence to the optimal policy in the long term. The proposed asynchronous advantage actor-critic with gradient sharing (A3C-GS) based SoC balancing approach trains the agents based on the output data of the multiple bidirectional DC–DC converter buck-boost circuit to avoid the use of vehicle dynamics and cumbersome operating modes that are difficult to accurately model. Furthermore, the DC bus voltage regulation is integrated simultaneously with the SoC balancing scheme. Comparison results based on simulating three/six batteries based EV system show that the proposed A3C-GS based SoC balancing scheme can achieve the highest steady-state rewards while the oscillation in the early training stage is larger resulted from a larger exploration range.

Active balancing circuit for advanced lithium-ion batteries used in photovoltaic application

An approach to the analysis and design of a bidirectional DC power converter for the cell voltage balancing control of a series connected lithium-ion battery string is presented in this paper. The proposed Cell Balancing Circuit (CBC) is designed to transfer the energy from the fully charged battery cell to the weakest one using a switch mode power converter operation. This operation maintains cell batteries at the same State-Of-Charge (SOC) and voltage range. Unlike previous battery balancing circuits, the balancing method uses only one magnetic component, resulting small size system. Simulation and experimental results show that the proposed cell balancing method can not only enhance the bidirectional battery equalization performance, but can also reduce the switching loss during the equalization period. Experiment results are provided to verify the operating principle of the proposed balancing method. Specific conditions of experiments are used to reproduce photovoltaic operations

Novel Active Battery Balancing Methodologies for Lithium Batteries: An Experimental Comparative Analysis

Inconsistency in the battery pack parameters results in an uneven state of charge (SoC). The active battery balancing method is an approach to equalize the SoC of the battery cells in a battery pack. In active balancing method, the battery having the highest SoC is made to equalize with the battery having the lowest SoC through the electronic circuits. However, it needs more cost and complex control circuits. To overcome this shortcoming, simple switching circuit‐based dynamic battery balancing techniques and row interconnected techniques are proposed. The proposed techniques are compared and analyzed with various conventional techniques. The experiments are conducted with 4.4 V, 6 Ah, 0.5 C lithium ferro‐phosphate battery cell and the battery pack consists of four cells. In the proposed techniques, the interconnections among the battery cells are altered using a switching matrix circuit. From the results, it is observed that the balanced row interconnected series–parallel dynamics and balanced row interconnected series–parallel have delivered superior performance under all the balancing conditions. Overall, the proposed technique enhances the battery storage capacity by 23.3% during the unbalanced SoC condition. The row interconnected series–parallel dynamics have achieved the average SoC of 96.14% under different balancing conditions.

Boosting Li-Ion Battery Pack Lifespan with Active On-Load Balancing

Due to the repeated cycles of charging and discharging, battery manufacturers cannot ensure perfect cell balance. Cell balancing is considered essential for equalizing each battery cell to the same state of charge level in a series configuration. Lithium-ion (Li-ion) batteries can be damaged or have their lifespan decreased by improper discharge processes. This study investigates battery balance during discharge by analyzing the state of charge (SoC) and current distribution of a 3-cell battery pack based on a multi-transformer shared flyback converter (F-C) under varying load conditions. A balanced approach is employed to control individual cells using a dedicated switch for each cell during the discharge process. The results indicate that the proposed active balancing method can enhance the Li-ion pack's balancing capacity while reducing the disparity in residual energy among the battery cells. The unique contribution of this research lies in the active balancing approach, which offers efficient and effective battery management during discharge. This approach provides crucial insights for the future development of improved battery systems. Therefore, Given the linearly decreasing target SoC, the average error over all time points is approximately 4.29%.

An Analysis and Optimization of the Battery Capacity Difference Tolerance of the Modular Multi-Level Half-Bridge Energy Storage Converter

As a power converter of battery energy storage, the multi-level converter and its battery balancing control have received much attention from scholars. This paper focuses on the modular multi-level half-bridge energy storage converter (MMH-ESC), including its topology, working principle, and pulse width modulation (PWM) methods. Under the battery balancing control strategy based on level-shifted carrier PWM (LS-PWM), formulas are derived and calculations are performed to get the charge or discharge of each submodule (SM), thereby obtaining the tolerance for capacity differences among these batteries. A range of battery capacity values that can maintain a balanced state is provided to enhance flexibility in battery configuration and utilization, avoiding the limitation of all batteries to the same capacity. Finally, a new bridge arm modulation wave allocation method is proposed. This method significantly expands the range of SM battery capacity selection and provides a high-tolerance modulation method for the converter under extreme or even fault conditions.

Loss and reliability analysis of various solid-state battery reconfiguration topologies

The research domain about the selection and design methodology of battery topology structures for energy storage systems, grounded in practical application scenarios, remains significantly underexplored. Furthermore, a substantial gap exists in the current state of research, where the majority of studies lack a comprehensive analysis of losses and reliability associated with reconfigurable battery topology structures. This paper quantitatively analyzes existing MOSFET-based topologies from three key dimensions: losses, costs, and reliability. The study aims to discern the impact of different topology structures and energy storage systems with redundant units on these three dimensions. Subsequently, while ensuring the adaptability of the topology structure, we propose a novel reconfigurable battery system topology suitable for DC microgrids, accompanied by its corresponding control strategy. Through comparative analysis with three typical topology structures, this topology structure has been validated to exhibit certain advantages in terms of losses, reliability, and costs. Lastly, the feasibility of the introduced topology structure is demonstrated through simulation using MATLAB/Simulink. Simulation results indicate that the proposed topology structure not only provides precise control of charge and discharge currents but also demonstrates excellent battery balancing capabilities.

An aging- and load-insensitive method for quantitatively detecting the battery internal-short-circuit resistance

Early-stage detection of the battery internal short circuit (ISC) can effectively prevent batteries from fire-related accidents. However, it is technically challenging because the current leakage signals at the beginning stage of the ISC could be submerged by the joint effect of battery aging, battery balancing, measurement noise, and highly dynamic charging/discharging behaviors. Aiming at these issues, we here propose an equalization-based method to quantitatively calculate short circuit resistance for pack applications. The relationship between the balanced capacity and short circuit resistance is mathematically derived and unified for both passive and active equalization systems. Battery-in-the-loop experiments show that when the short-circuit resistance changes from 55 to 330 Ω, the error of our prediction can be well-bounded within ±2%, outperforming most existing algorithms. Further, the computational burden of the proposed method is similar to that of the Ah-counting method, requiring no additional information on the batteries’ aging status. Since our method supports arbitrary load profiles, it can be used in a wide range of applications such as electrified vehicles and renewable energy storage systems.

Artificial neural network-enabled approaches toward mass balancing and cell optimization of lithium dual ion batteries

Dual ion batteries (DIBs) are gaining prominence as alternate energy storage devices in recent years due to their high operating potential and low cost. For an all-carbon based DIB, owing to the low cathode capacity, the anode:cathode mass ratio has a much more significant effect on the overall cell performance. Achieving a generalized model towards optimization of active mass balancing in these devices still remains a challenge. With an aim to accelerate the development of dual ion batteries, herein, we attempt to make an experimental data-driven deep neural network model towards mass balancing and cell optimization of a graphite-graphite lithium dual ion battery. We designed appropriate experimental conditions with maximum ranges of control variables and performed detailed electrochemical studies. The data generated through such a minimum number of experiments are used to predict the performance characteristics of the graphite/graphite-based lithium dual ion full cell under a wide range of active electrode mass ratios and current densities, through a machine learning approach. We demonstrate that our model can predict the charge-discharge profiles of the full cell at any given current density in the range 50 mA g−1 and 1 A g−1. Further, using these charge-discharge profiles, we find the discharge capacities of the cell for varying mass ratios and different mass loading. Though we address here the case of graphite/graphite lithium dual ion battery cells, the approach can easily be extended to other battery chemistries to achieve accelerated development of advanced energy storage devices.

Improved Battery Balancing Control Strategy for Reconfigurable Converter Systems

In order to address the issue of battery cell disparity in lithium-ion battery systems, battery balancing techniques are required. This paper proposes an improved battery balancing strategy within a reconfigurable converter system. The strategy is based on the state of charge (SOC) of batteries, and utilizes the reconfigurable converter system to transfer energy from battery modules with high SOC to those with lower SOC. Additionally, it allows for battery module balancing while supplying power to loads. A MATLAB/Simulink simulation model with five batteries was built to validate the effectiveness of the proposed balancing strategy under unloaded and loaded conditions. The simulation results demonstrate that the proposed strategy achieves more efficient and accurate battery module balancing compared to the previous balancing modes.

Equalization technology of special vehicle power battery pack

In special vehicles, single cells or battery packs often provide energy for the vehicle after being connected in series and parallel. However, due to the influence of the single battery production process and the use environment, inconsistencies may occur in the battery pack, resulting in a decline in the performance of the battery pack. Therefore, the battery balance management system has increasingly become an indispensable module in the battery management system. It can perform real-time balanced management of the battery pack according to the battery pack status information, thereby avoiding the expansion of inconsistency, improving the capacity utilization rate of the battery pack, slowing down the aging speed of the battery pack, and increasing the driving mileage of the vehicle. To sort out and summarize the current development of battery pack balancing system, based on a large number of references, this paper studies and analyzes the mechanism of inconsistency, the commonly used equalization topology and control strategy of lithium power battery pack. And finally, the development trend of battery pack equalization technology for special vehicles is prospected.

Multi LiFePO4 Battery Balancer for further Developing Effectiveness and Enhanced Capacity

Multi LiFePO4 Battery Balancer for further Developing Effectiveness and Enhanced Capacity

Method of creation of power sources for home appliances under constraints of limited resources

The subject of study in this article is the voltage ranges, methods, and tools for prototyping independent sources of power supply and artificial lighting for home appliances with reuse of only widespread components. The goal is to improve the efficiency of the creation and use of independent power supply sources for home appliances. Task: to analyze the history of the development of voltage standards for households; analyze existing autonomous power sources and types of batteries; analyze different loads; find rational voltage ranges based on fundamental values; analyze charge control and balancing circuits for lithium-based batteries; propose the technique of prototyping independent sources of power supply based on reused lithium-ion (Li-ion) accumulators; provide an example of the practical application of the results of research. According to the tasks, the following results were obtained. The evolution of voltage standards of electrical supply networks is analyzed. Types of autonomous power supplies, including pure sine versions, are discussed. The analysis of batteries for autonomous power sources of different chemical compositions is performed. It is proposed to use the water analogy of current and area as an analogy of battery capacity for visual representation of electrical processes. Models of constant current consumption and constant power consumption are considered. It is proposed to reduce the internal resistance of the battery assembly by parallel connection of the reused lithium-ion accumulators. Correspondence of voltage ranges of sequential connection of lithium-ion cells to ensure compatibility with existing devices is investigated. Rational parameters of voltage ranges to ensure compatibility of lithium-ion and acid accumulators with the ability to charge directly from solar panels without a charge controller are found. Charge controllers, battery management systems (BMS), and battery balancing circuits are analyzed. A set of steps for reuse of lithium-ion accumulators for the creation of autonomous power sources is proposed. Conclusions. The main contribution of this research is the proposed method of creation of power supply and interior lighting based on the reuse of accumulators without additional components. The discovered and proposed magic numbers of 3, 5, 7, 9, 11 and 13 for series connection of lithium-ion cells allows to obtain the equivalent of standard voltage ranges of 12 V, 19 V, 27 V, 36 V, 42 V and 48 V. The proposed technique of adjusting the voltage of the passive balancer allows adding 4.5 % to the capacity of the battery assembly. The described solutions allow to build the completely scalable autonomous low-voltage electrical supply network with the ability to charge directly from solar panels without expensive charge controllers.

Transmission of Power and Signal Multiplex for Electric Vehicles Using Cascaded Multilevel Inverters

Abstract: P&SMT, or power and signal multiplex transmission, is a method for transmitting communication signals using power electronic circuits. A three-phase cascaded multilevel inverter-based P&S MT system is recommended in this investigation. By allowing communication signals to be transmitted without utilizing a Controller Area Network bus, the proposed solution can lower the wiring expense of the existing electric vehicle (EV) communication system. The system's architecture enables battery balancing discharge and motor speed management for EVs. In a simulation system proposed in MATLAB/Simulink, both power and communication signals are effectively conveyed using the combined pulse width modulation scheme and frequency shift keying approach. The maximum signal rate of the proposed system is established at 600 bits per second by analyzing the bit error rate of the sent signal.

Evaluation of Current-Mode Controller for Active Battery Cells Balancing With Peak Efficiency Operation

This article presents a current-mode controller for switched-inductor topology to achieve voltage balancing between battery cells or modules in a battery pack while operating at peak efficiency. The presented method yields several advantages and/or eliminates several drawbacks of the existing conventional fixed duty cycle scheme. Among these advantages: 1) the balancing current is well controlled instead of being a function of battery cells’ voltages and system parasitic elements, which might result in exceeding the current ratings of the components, and 2) the balancing current reference is selected such that the balancing circuit operates at its maximum efficiency point and, therefore, yielding lower balancing power losses. This article also presents a battery balancing algorithm for utilization with the presented controller that achieves open circuit voltage balancing, which is a more accurate indicator of state-of-charge compared to terminal voltage. Experimental results obtained from a laboratory prototype of a three-cell battery pack are presented to evaluate the presented current control and balancing method under different modes of operation.

Validation of a balancing model based on master-slave battery management system architecture

The battery management system (BMS) performs the monitoring and control of the charging/discharging process of the cell, state of charge estimation, battery safety and protection, state of health estimation, cell balancing, and thermal management. These control operations ensure accurate, safe, and reliable operating conditions, individual cell damage on battery string, and increase the cell life. Battery balancing is one of the key technologies in the BMS, which affects the actual usable capacity range, performance, and lifetime of the entire battery module. However, it is difficult to evaluate or compare the performance of the overall BMS under the multi-series battery module structure. Most of the proposed battery energy storage system (ESS) models focus on energy distribution and system estimation (microgrid or renewable energy). This study develops a balancing model for estimating the balancing performance of the BMS. A Master-Slave BMS (MS-BMS) is proposed to validate the balancing model. The Master and Slaves of the BMS employed a traditional flyback converter with a MOSFET switching array and bidirectional flyback converters with photoMOS arrays, respectively, to perform the balancing behavior. The balancing skill, balancing circuit power, equalization speed, control simplicity, modularization simplicity, and cost has been considered in designing the proposed BMS. The simulation results are verified with the experimental results, which are then compared with the balancing model's results under the five balancing conditions, and the average absolute error of the balancing duration results is 3.12%. The performance of the proposed BMS is also compared with the existing modular BMS architecture, which validates the advantages of the proposed BMS including equalization speed, control simplicity, modularization simplicity, and cost.