Search

Lithium‐ion cell chemistries are favored in the automotive sector, as they enable electric vehicles (EVs) to compete with traditional gasoline‐powered vehicles in terms of performance, range, and cost. The life and performance of these packs depend upon the Battery management system which monitors and controls the pack. The modeling, simulation, and analysis of a lithium‐ion battery pack that closely resembles an actual automobile battery are the focus of this paper. Real cells that are commercially available and specifically developed for automotive applications are modeled in the simulation environment. The cell characterization and formation of pack topology with heat exchange are addressed. A commercial electric car's power train model and EV dynamics are used in the simulation environment to test the modeled battery pack over various drive cycles. The performance analysis is upscaled by considering different aspects like resistive forces while driving, ambient temperature, initial conditions while the vehicle starts, etc. The battery manufacturer can verify the battery's performance under different load conditions, with a high degree of similarity to real‐world scenarios. The simulations are conducted on MATLAB/Simulink 2021b software. [ABSTRACT FROM AUTHOR]

Batteries are essential to mobilization and electrification as they are used in a wide range of applications, from electric vehicles to small mobile devices. All these devices are powered with AC or DC inside their systems, so they require different battery systems depending on their technical requirements. Batteries show unique characteristics depending on their types, and their needs vary based on their performance, ambient conditions, and so forth. One of the main demands for them is thermal stability. For batteries, thermal stability is not just about safety; it's also about economics, the environment, performance, and system stability. This paper has evaluated over 200 papers and harvested their data to build a collective understanding of battery thermal management systems (BTMSs). These studies are specifically designed to solve different problems. This paper has been prepared to show what these systems are, how they work, what they have been designed for, and under what conditions they should be applied. The BTMSs have been evaluated based on their method, method tools, discharge rate, maximum temperature, temperature difference values, and ambient and inlet temperatures. After evaluating over 200 studies, the results indicate that the passive BTMSs are not useful the cases where the temperature reaches higher values suddenly, especially for system systems that require higher discharge rates. On the other hand, active cooling methods do not manage the temperature difference in the battery cells. However, hybrid cooling methods address both cases admirably by compensating for both of their weaknesses and bringing out their advantages. The general optimum temperature for lithium battery batteries is 55°C. Even though there are many other parameters that need to be considered before making a decision for a BTMS design, the best performance for an optimum system seems to be methods 34, 38, and 22 as they are able to provide lower maximum temperature and temperature difference in the cells. [ABSTRACT FROM AUTHOR]

The transportation sector is under increasing pressure to reduce greenhouse gas emissions by decarbonizing its operations. One prominent solution that has emerged is the adoption of electric vehicles (EVs). As the electric vehicles market experiences rapid growth, the utilization of lithium-ion batteries (LiB) has become the predominant choice for energy storage. However, it is important to note that lithium-ion battery technology is sensitive to factors, like excessive voltage and temperature. Therefore, the development of an accurate battery model and a reliable state of charge (SOC) estimator is crucial to safeguard against the overcharging and over-discharging of the battery. Numerous studies have been conducted to address lithium-ion battery cell modeling and SOC estimations. These studies have explored variations in the number of RC networks within the model and different estimation methods. However, it is worth mentioning that the capacity of a single lithium-ion battery cell is relatively low and cannot be directly employed in electric vehicles. To meet the total capacity and voltage requirements for electric vehicles, multiple cells are typically connected in series or parallel configurations to form a battery pack. Surprisingly, this aspect has often been overlooked in previous research. To tackle this overlooked challenge, our study introduces a comprehensive battery pack model and an advanced Battery Management System (BMS). We then integrate these components into an electric vehicle model. Subsequently, we simulate the integrated EV-BMS model under the conditions of four different urban driving scenarios to replicate real-world driving conditions. The BMS that we have developed includes an Extended Kalman Filter (EKF)-based SOC estimation system, a mechanism for controlling coolant flow, and a passive cell-balancing algorithm. These components work together to ensure the safe and efficient operation of the battery pack within the electric vehicles. [ABSTRACT FROM AUTHOR]

Electric powered vehicle popularity gives us better option for reducing the hydrocarbon emissions for the clean environment and will help to minimizing the troposphere of ozone degradation. Evs that are powered by batteries are becoming more commonplace worldwide. A strong Battery Management System (BMS) is essential for the reliable and safe operation of batteries, which have been widely used in many large power applications, including EVs and hybrid EVs. Their optimal plan and the management are significant for safe and beneficial tasks. This review paper examined with about the oldest kind of battery-latest powered battery (Pb-acid battery) and the most recent innovation of battery, lithium-ion battery. The present paper deals about the recent improvement in three important areas like Battery pack shape, different battery material and thermal behaviour which covered main challenges for EVs operation. [ABSTRACT FROM AUTHOR]

In this study, the battery pack and ESP32 microcontroller-based battery management system (BMS) design for the electric bicycle have been carried out. The software updates were realized when the battery pack was in the box, thanks to the built-in Wi-Fi feature of the ESP32. The voltage values were read precisely, and a stable BMS was created with a 12-bit ADC-based ESP32 controller. The battery had temperature control from 7 different points. The temperature data was received from DS18B20 digital temperature sensors, and the charging current was cut off when the threshold value was exceeded. At the same time, the ACS712 5A current sensor was used to determine and prevent the excessive current draw. The charging current was defined as 2A. BMS cuts off the charging current to protect the battery pack when the charging current exceeds 3A. The resistor used for passive balancing in BMS was isolated from the ESP module with the KPS2801 optocoupler. The voltage of the battery pack was charged from 3.7 V to 3.85 V in the real-time test. The charging process continued for one hour, and the voltage changes of each cell were obtained in 10-minute periods. It was observed that all cells were charged in a balanced way at the end of the charging process. Thus, the charging process of the designed battery pack was carried out successfully through the designed BMS. [ABSTRACT FROM AUTHOR]

In the last decades of electric vehicle (EV) development, battery thermal management has become one of the remaining issues that must be appropriately handled to ensure robust EV design. Starting from researching safer and more durable battery cells that can resist thermal exposure, battery packing design has also become important to avoid thermal events causing an explosion or at least to prevent fatal loss if the explosion occurs. An optimal battery packing design can maintain the battery cell temperature at the most favorable range, i.e., 25–40 °C, with a temperature difference in each battery cell of 5 °C at the maximum, which is considered the best working temperature. The design must also consider environmental temperature and humidity effects. Many design strategies have been reported, including novel battery pack constructions, a better selection of coolant materials, and a robust battery management system. However, those endeavors are faced with the main challenges in terms of design constraints that must be fulfilled, such as material and manufacturing costs, limited available battery space and weight, and low energy consumption requirements. This work reviewed and analyzed the recent progress and current state-of-the-art in designing battery packs for superior thermal management. The narration focused on significant findings that have solved the battery thermal management design problem as well as the remaining issues and opportunities to obtain more reliable and enduring batteries for EVs. Furthermore, some recommendations for future research topics supporting the advancement of battery thermal management design were also discussed. [ABSTRACT FROM AUTHOR]

In this paper, the temperature response of a lithium‐ion type 18650 battery pack cooled by a thermoelectric air‐cooling module is presented. The effects of the airflow rate, on‐off cooling fan position, charging and discharging rate and cooling by the thermoelectric air‐cooling module are investigated. The charging and discharging procedures with different current rates of 2 A (0.06 C), 3 A (0.09 C), and 4 A (0.12 C) are investigated. The results showed that different test conditions of the thermoelectric air‐cooling module have a substantial effect on the temperature of the battery pack. It was demonstrated that a thermoelectric air‐cooling module has a decreased battery temperature of lower than 40°C. The operating conditions of the cooling fans have a substantial effect on battery temperature. The experiment in which all the cooling fans are turned on shows a higher cooling capacity than natural air cooling by approximately 16%–57%. However, when setting the on‐off position of the fans that are installed in different positions, the cooling capacity when the fans at the inlet and thermoelectric cooling heat sink are turned on and the fan at the outlet battery pack is turned off is slightly less than that when all the cooling fans are turned on by approximately 25%–57%. Therefore, it can be selected as an optimum for cooling the battery pack due to less power consumption and noise issues. The proposed research can be implemented as a guideline for the cooling system of energy storage, such as small electric vehicle platforms, ground batteries, and solar energy storage. [ABSTRACT FROM AUTHOR]

This article presents an efficient and fast echelon battery equalization method based on wide voltage range bidirectional converter combined with DBSCAN (density-based spatial clustering of applications with noise) clustering control strategy. Thanks to the wide voltage range and bidirectional buck-boost characteristics of the four-switch bidirectional converter, the battery energy can be reasonably redistributed between the battery and the super capacitor. The converter operating in synchronous rectification mode can not only achieve bidirectional energy flow in a wide voltage range, but also has a high energy conversion efficiency. The DBSCAN clustering algorithm is used to divide all battery cells into groups, and each group may contain one or more adjacent and nonadjacent battery cells. First, the nonadjacent single cells are balanced and integrated into adjacent group with the closest voltage. Then, the groups with different voltages are balanced by group-to-group, thereby realizing rapid balance of the entire battery pack. In order to verify the effectiveness of the proposed method, simulations and experimental verification were carried out. The experimental results show that, comparing with traditional battery balancing methods, the proposed method achieves shorter balancing time and higher balancing efficiency. [ABSTRACT FROM AUTHOR]

• Battery thermal management is studied with phase-change materials and heat pipes; • Phase change materials improve the temperature uniformity of the battery pack; • Phase change-heat pipe cooling reduces by 22.3% battery temperature than using air; • Phase change material RT31 reduces by 11.8 % battery temperature at 5–50 W·m−2·K−1; • Short circuit of combination cooling reduces by 29.9% temperature than air cooling. Lithium-ion battery packs generate high-level heat under harsh and rigorous conditions. The inadequate heat dissipation results in high pack temperature above the safe operating range. This study investigates an efficient and cost-effective battery thermal management system based on phase change materials and a micro heat pipe array. The battery is treated as a single domain. A battery pack with six series stacked batteries is analyzed using the Newman-Tiedemann-Gu-Kim model. The thermal performance of a battery thermal management system is analyzed using phase change materials with various melting temperature values, ambient temperature, and convective heat transfer coefficients of micro heat pipe arrays. Results show that the maximum temperature of the cooling system with micro heat pipe arrays and phase change materials is 33.8 °C, which is reduced by 22.3 % and 7.8 % compared to the air-cooled and cooling system with micro heat pipe arrays. At forced convection of 50 W·m−2·K−1, the maximum battery temperature values for the phase change material RT31, RT35, and RT42 are reduced by 11.8 %, 8.9 %, and 5.4 % compared to those at forced convection of 5 W·m−2·K−1. Under short-circuit conditions, the cooling system with micro heat pipe arrays and cooling system with micro heat pipe arrays − phase change materials reduce the maximum battery temperature by 12.4 % and 29.9 % compared to the air-cooled system. Results show that the developed model for the battery thermal management system provides a reference for designing phase change materials with micro heat pipe arrays. [ABSTRACT FROM AUTHOR]

Saving energy is a fundamental topic considering the growing energy requirements with respect to energy availability. Many studies have been devoted to this question, and life cycle assessment (LCA) is increasingly acquiring importance in several fields as an effective way to evaluate the energy demand and the emissions associated with products' life cycles. In this work, an LCA analysis of an existent lithium-ion battery pack (BP) unit is presented with the aim to increase awareness about its consumption and offering alternative production solutions that are less energy intensive. Exploiting the literature data about cradle-to-grave and cradle-to-gate investigations, and after establishing reasonable approximations, the main BP sub-elements were considered for this study, such as the plastic cells support, the Li-ion cells brick, the PCBs for a battery management system (BMS), the liquid-based battery thermal management system (BTMS) and the BP container. For each of these components, the impacts of the extraction, processing, assembly, and transportation of raw materials are estimated and the partial and total values of the energy demand (ED) and global warming potential (GWP) are determined. The final interpretation of the results allows one to understand the important role played by LCA evaluations and presents other possible ways of reducing the energy consumption and C O 2 emissions. [ABSTRACT FROM AUTHOR]

Electric vehicles are a clean energy transportation option recently emerged as an alternative to the conventional engine powered vehicles. These vehicles are using Lithium ion battery as energy storage for their propulsion because of its energy density. Due to the chemical reaction of battery elements and internal resistance, the battery releases heat during charging and discharging. Unless this heat is controlled to be within the battery optimum operating temperature, the battery performance and life will be seriously affected. This paper is dedicated to conduct fundamental studies on the battery cooling. A three dimensional numerical analysis is made using PHOENICS version 2018. Cylindrical type battery cell is used in this study. The study gives insight to thermal response, flow field and temperature profiles in the battery module with air flow direction relative to battery cell orientation and cell arrangement. Temperature variation along the flow, and transverse direction of the battery pack is discussed. With a 5 mm inter cell spacing and symmetric arrangement, maximum cell to cell temperature variation in the axial flow type is observed to be 0.2 °C, while in the radial flow type about 3.5 °C for same arrangement. Quantitative and qualitative results obtained from the numerical test are presented. Furthermore, this work is believed to contribute to the improvement of battery air cooling system design in such a way the associated cost and efficiency is compromised. [ABSTRACT FROM AUTHOR]

Copyright of Electric Machines & Control / Dianji Yu Kongzhi Xuebao is the property of Electric Machines & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Summary: The parallel air‐cooled system is commonly applied in electric vehicles to cool the battery pack, in which flow pattern significantly influences the system cooling performance. In this paper, the curved divergence and convergence plenums are used to design the flow pattern in the parallel air‐cooled system for battery thermal management. The computational fluid dynamics (CFD) method is used for performance evaluation of the cooling system. The height distribution of control points is used to describe the plenum shape. During the optimization process, flow resistance network model is employed to obtain the velocity distribution of the system. An effective strategy is developed to adjust the height distribution of the control points for flow pattern design. Experiments are conducted to verify the CFD method and calculation model. Then typical cases are adopted to evaluate the proposed strategy for flow pattern design. The numerical results show that the strategy can effectively control the system flow pattern by designing the plenum shape. The cell temperature difference of the optimized system achieves an 86% reduction with the pressure drop only increased by 26%. Furthermore, compared with the optimized system with linear plenums in the reference, the optimized system with curved plenums achieves 48% reduction for the cell temperature difference without the pressure drop increased. Finally, experiments are conducted for the optimized system to verify the effectiveness of the developed strategy. The present study can provide a guide for the design of efficient parallel air‐cooled BTMS. Highlights: Shape optimization of the curved plenums for air‐cooled BTMSs is conducted.Effective strategy is developed to optimize the shape of curved plenums.ΔTmax of the optimized BTMS is reduced by 86% with ΔP only increased by 26%.Optimized BTMS with curved plenums performs better than that with linear plenums.Experiments are done to verify the calculation models and optimization strategy. [ABSTRACT FROM AUTHOR]

With the increasing scale of battery systems, the impact of battery inconsistency due to aging on battery pack performance becomes increasingly significant. To achieve high-precision battery pack modeling, we propose an in-situ estimation method for battery inconsistency parameters. The proposed method utilizes current and voltage data recorded by the battery management system (BMS). The respective terminal voltage errors are used as the loss function, and the equivalent circuit model and the fully connected neural network are combined to realize the estimation of inconsistency parameters. Through optimization algorithm, the inconsistency parameters of all cells in the battery pack are simultaneously estimated. The estimation results of full capacity, high-end capacity, and internal resistance exhibit high accuracy with root-mean-square error (RMSE) values of 0.82% (0.393 Ah), 0.70% (0.336 Ah), and 3.34% (0.097 m Ω), respectively. The battery pack model constructed using the estimation results maintains high accuracy across various operating conditions, demonstrating the effectiveness of the proposed method for inconsistency estimation and battery pack modeling. • Estimate the battery inconsistency parameters based on the similarity of the battery SOC-OCV curves with the BMS data. • Combine the neural network and equivalent circuit model to simultaneously estimate the capacity, internal resistance and SOC parameters of each cell in the battery pack. • The accuracy of the proposed method was demonstrated by comparing measured parameters with estimated parameters, and the effectiveness was further demonstrated by battery pack model simulation results. [ABSTRACT FROM AUTHOR]

Purpose: Battery electric vehicles (BEVs) have been widely publicized. Their driving performances depend mainly on lithium-ion batteries (LIBs). Research on this topic has been concerned with the battery pack's integrative environmental burden based on battery components, functional unit settings during the production phase, and different electricity grids during the use phase. We adopt a synthetic index to evaluate the sustainability of battery packs. Methods: A life cycle assessment (LCA) is used to reveal the aspects of global warming potential (GWP), water consumption, and ecological impact during the two phases. An integrative indicator, the footprint-friendly negative index (FFNI), is combined with footprint family indicators of battery packs and electricity sources. We investigate two cases of 1 kg battery production and 1 kWh battery production to assess nickel–cobalt–manganese (NMC) and lithium–iron phosphate (LFP) battery packs and compare their degrees of environmental friendliness. Then, we break down the battery pack to identify the key factors influencing the environmental burden and use sensitivity analysis to analyze the causes. Moreover, we evaluate the environmental impact of battery packs during the use phase among different regions. Results and discussion: Regardless of the functional unit (FU), the weights of the carbon footprint (CF), water footprint (WF), and ecological footprint (EF) are approximately the same. The results of the integrative environmental indicator, the FFNI, illustrate that the LFP is approximately 0.014, which is lower than that of the NMC battery pack in the mass production case. When using energy units as the FU, the FFNI of the NMC is 0.015, which reflects a lower environmental burden than that of other battery packs. In the use phase, 1kWh electricity consumption in China and Europe has the highest and lowest FFNI, respectively. When breaking down the battery-pack components, the simplified model advocates the cathode as the major contributor that determines the total environmental performance. In the following sensitivity analysis, the battery management system (BMS) is found to be the most intensive part of the footprint of most battery packs. Conclusion: FU can influence the evaluation results. Developing proper renewable energy sources can reduce the footprints of battery packs during the use phase. The positive electrode pastes in the battery cell, BMS, and packaging in the battery pack can influence the environmental burden. Adopting green materials in sections like the BMS may be a specific measure to enhance the environmental friendliness of a battery pack during the production phase. [ABSTRACT FROM AUTHOR]

This study presents a multidisciplinary end-to-end design, build, and test drive experience of a Formula Society of Automatic Engineers (FSAE) electric vehicle. The design team members’ background include computer engineering, electrical engineering, and mechanical engineering expertise. Each team member worked on a sub-team namely mechanical, drivetrain, supervisory control and data acquisition (SCADA), and battery management system (BMS). The mechanical team modified/redesigned a gasoline FSAE car frame to accommodate the battery pack, cooling systems, electric drive train, and SCADA hardware. The drivetrain team designed a combinational logic-based tractive system control board to enhance the safety and reliability of the drivetrain. The SCADA team used a model-view-controller software architecture and agile development practices to design and implement a custom electric vehicle operating system and the main brain hardware. The BMS team designed the sensing network and communication protocol to provide an update on the state of the health of the energy source. A thorough description of each sub-system is provided herein. System integration and field test results are also included.

It is more convenient and safer to employ wireless power transfer (WPT) systems to charge the battery pack of electric scooters (ESs) than conventional plug-in systems. A charging equaliser suitable for ESs is proposed to achieve constant current (CC) output without communication link between the transmitter side and the receiver side. The full-bridge rectifier and select switches utilised at the receiver side are employed to be operated once to change from the balancing mode to charging modes. The characteristics of the load-independent current output in the CC mode are achieved by properly selecting the parameters of the circuit so that no sophisticated control strategies are required to regulate the output as per the charging profile. The experimental results show that when the voltage of battery pack is charged at 32 or 4.2 V, the current is 1.02 or 1.12 A, respectively. Therefore, the proposed system can be considered as a CC system. [ABSTRACT FROM AUTHOR]

This study presents a multidisciplinary end-to-end design, build, and test drive experience of a Formula Society of Automatic Engineers (FSAE) electric vehicle. The design team members' background include computer engineering, electrical engineering, and mechanical engineering expertise. Each team member worked on a sub-team namely mechanical, drivetrain, supervisory control and data acquisition (SCADA), and battery management system (BMS). The mechanical team modified/redesigned a gasoline FSAE car frame to accommodate the battery pack, cooling systems, electric drive train, and SCADA hardware. The drivetrain team designed a combinational logic-based tractive system control board to enhance the safety and reliability of the drivetrain. The SCADA team used a model-view-controller software architecture and agile development practices to design and implement a custom electric vehicle operating system and the main brain hardware. The BMS team designed the sensing network and communication protocol to provide an update on the state of the health of the energy source. A thorough description of each sub-system is provided herein. System integration and field test results are also included. [ABSTRACT FROM AUTHOR]

To solve the problems of ampere-hour integration method for battery packs with inaccurate state of charge (SOC) estimation due to sensor accuracy, battery aging, integration error and initial value, the parameters of SOC initial value, nominal capacity and integration period of the traditional ampere-hour integration were improved. The first-order RC equivalent circuit model was established based on the internal relationship between the SOC and the open circuit voltage (Uo). In the circuit model, the Uo was extracted and updated in real time by the recursive parameter-free least squares (PF-RLS) with forgetting factor. The temperature with crucial effect on Uo was considered, and a three-dimensional model of SOC-Uo-θ was established to provide an accurate initial value for the improved ampere-time integration method. Based on the inconsistency of battery pack, the maximum voltage and the minimum voltage fusion algorithm were proposed， and the federal urban driving schedule（FUDS) working condition detection and the real vehicle working condition verification were carried out. The results show that the accuracies of the PF-RLS online extraction of Uo, the single cell SOC and the battery pack SOC algorithm are respective 2.55%, 3.20% and 4.00%, which meets the technical requirements of QC/T 897—2011 battery management system for electric vehicles claim. [ABSTRACT FROM AUTHOR]

Enhanced battery pack cooling remains an open thermal management challenge in hybrid electric vehicle applications. A robust cooling system should maintain the battery pack core temperature within a prescribed operating range to improve system performance, durability, and reliability while minimizing power consumption. This paper proposes a smart battery thermal management system utilizing heat pipes as a thermal bus to efficiently remove heat. The system couples a standard air conditioning system with traditional ambient air ventilation. The two loops can run independently or in tandem to achieve the desired control. A nonlinear model predictive controller was developed to maintain the battery core temperature within a designated range using the compressor and fan speeds as the control inputs. A mathematical battery thermal model was developed to estimate the core and surface temperatures. The system performance and power requirements were evaluated for various driving cycles and ambient conditions. Numerical results showed that the proposed cooling system can regulate the battery core temperature within the desired temperature range (maximum tracking error of 2.1°C) while compensating for ambient temperature conditions using a suitable cooling strategy. The simulation results showed the ability to remove up to 1135 kJ of heat. The simulation also presents the power consumed by system components under varying modes and ambient conditions. [ABSTRACT FROM AUTHOR]

A pack of batteries is one of the most important and expensive assemblies for an electric vehicle. A pack of batteries is comprised of several batteries connected in series. The number of the batteries connected depends on the operating voltage of the vehicle's on-board system as well as on the individual characteristics of the batteries used, e.g. the operating voltage of a single cell. One or several cells of a pack of batteries could be damaged if improperly exploiting an electric vehicle- excessively discharging the batteries or overloading the electric vehicle. If a self-converted vehicle does not use an intellectual BMS (battery management system) that can identify and register voltage drop for any individual cell in the high-load regime, e.g. when accelerating, it is difficult to identify and change the cells damaged. In case a cell does not demonstrate a complete failure, it is almost impossible to identify a defect in any regime other than the load regime. The research developed and compared three different methods for identifying defective battery cells. The methods were approbated on a converted Renault Clio. The experiment involved making voltage measurements in road tests, running the electric vehicle on a roll test bench and making voltage measurements of maximally discharged batteries in the no-load regime. A comparison of the measurement results revealed that the measurements made in the road tests were the most accurate and useful. After the experiment, the defective battery cells were replaced, thereby restoring the performance of the battery pack. [ABSTRACT FROM AUTHOR]

Summary: State evaluation of battery pack is essential for battery management but laborious when dealing with massive information of cells within the pack. A graphical model for evaluating the status of series‐connected Li‐ion battery pack is established to release the burden. The model is founded by a 2D diagram, with the electric quantity "E" and the capacity "Q" as its axes, therefore called by the "E‐Q diagram." The new graphical diagram presents the dynamics of cell variations in a linear way, thereby benefiting the design and management of battery pack, including (1) quantifying the cell variations by region, (2) illustrating the evolution of cell variations during aging, (3) guiding the estimation of pack states considering algorithm error in cell states, and (4) solving the balancing problem. The experimental results conform to the theoretical analysis, indicating that the E‐Q diagram will be pervasively applied in the design and management of series‐connected battery pack. Moreover, the E‐Q diagram is suitable for education on the basics of a battery pack, because it is a graphical model. Novelty statements: This paper builds a novel graphical model for evaluating the status of series‐connected battery pack. The model can vividly present the cell variations of a battery pack in 2D diagram, named the E‐Q diagram. Error propagation from the cell state estimation to that of the pack and strategies for cell balancing are clearly interpreted by the graphical model. [ABSTRACT FROM AUTHOR]

• Diverging channel design cooling plate with oblique fins is newly proposed. • Thermal unbalance of the battery module is improved using the proposed design. • Cell-to-cell temperature difference in the pack cooling is decreased by 19.07%. • The pumping power to satisfy the temperature conditions is decreased by 67.8%. In this study, the thermal and hydraulic performances of a battery thermal management system are investigated in terms of the design of the cooling plate. A diverging channel with oblique fins (DCOF) cooling plate is newly proposed to overcome the limitations of the conventional straight channel cooling plate. The diverging design is applied to control the coolant velocity and heat transfer area, with oblique fins inserted to enhance the heat transfer efficiency. A simulation model of the battery and cooling system is developed and experimentally validated. When the DCOF design is applied to the battery module, the temperature uniformity is improved in terms of the temperature difference and standard deviation. As the investigation is extended from the module to the battery pack, the temperature difference and temperature standard deviation in the battery module are improved by 19.07% and 27.14%, respectively. Considering the power consumption of the cooling system, as the thermal performance of the DCOF design and baseline design is maintained, the power consumption of the coolant pump of the DCOF design is significantly reduced by 67.8%. [ABSTRACT FROM AUTHOR]

Vehicle battery systems are usually designed with a high number of cells connected in parallel to meet the stringent requirements of power and energy. The self-balancing characteristic of parallel cells allows a battery management system (BMS) to approximate the cells as one equivalent cell with a single state of health (SoH) value, estimated either as capacity fade (SoH E ) or resistance increase (SoH P ). A single SoH value is however not applicable if the initial SoH of each cell is different, which can occur when cell properties change due to inconsistent manufacturing processes or in-homogeneous operating environments. As such this work quantifies the convergence of SoH E and SoH P due to initial differences in cell SoH and examines the convergence factors. Four 3 Ah 18650 cells connected in parallel at 25 °C are aged by charging and discharging for 500 cycles. For an initial SoH E difference of 40% and SoH P difference of 45%, SoH E converge to 10% and SoH P to 30% by the end of the experiment. From this, a strong linear correlation between ΔSoH E and ΔSoH P is also observed. The results therefore imply that a BMS should consider a calibration strategy to accurately estimate the SoH of parallel cells until convergence is reached. [ABSTRACT FROM AUTHOR]

One of the most important parts of a Formula Student Electric race car is a battery pack, which includes accumulators and a battery management system. Difficult operating conditions in a racecar require careful approach to battery pack design, from choosing accumulator cells to mathematical modeling. The developed design procedure allows choosing an optimal battery pack design based on given initial parameters [ABSTRACT FROM AUTHOR]

Variations in cell properties are unavoidable and can be caused by manufacturing tolerances and usage conditions. As a result of this, cells connected in series may have different voltages and states of charge that limit the energy and power capability of the complete battery pack. Methods of removing this energy imbalance have been extensively reported within literature. However, there has been little discussion around the effect that such variation has when cells are connected electrically in parallel. This work aims to explore the impact of connecting cells, with varied properties, in parallel and the issues regarding energy imbalance and battery management that may arise. This has been achieved through analysing experimental data and a validated model. The main results from this study highlight that significant differences in current flow can occur between cells within a parallel stack that will affect how the cells age and the temperature distribution within the battery assembly. [ABSTRACT FROM AUTHOR]