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Summary: The performance of lithium‐ion (Li‐ion) batteries in a battery module is significantly affected by the operating temperature. Temperatures above 40°C can speed up the battery aging and shorten the lifespan and may even lead to thermal runaway. Besides, the maximum temperature deviation between the cells inside the battery module is normally expected to be less than 5°C. Among various cooling strategies used in thermal management of Li‐ion batteries, application of micro heat pipe arrays (MHPAs) has received little attention. Hence, in the present study, a feasibility study has been conducted to assess the thermal performance of such a thermal link in controlling both the maximum temperature and temperature dispersion within the desired range. The MHPA‐assisted cooling system was tested under various rates of heat generations (10‐25 W total) and degrees of inclination (−90° to +90°). Experimental results have revealed a significant influence of the MHPA angle of inclination on the temperature of the evaporating section of the heat pipe. The best thermal performance was found to be at an angle of inclination of −15° where the condenser is located above the evaporating section. Performance degradation was observed for all the MHPA orientations where the condenser is located below the evaporating section. The thermal performance of the MHPA‐assisted cooling system is also influenced by the rate of generated heat. The maximum effective thermal conductivity for the MHPA was measured to be about 75 000 W/m2 °C. A dimensional figure of merit is defined for the MHPA‐assisted cooling system. [ABSTRACT FROM AUTHOR]

Summary: As an energy storage component of an electric vehicle, the battery pack is subject to continuous vibration when working. It is very important to analyze the dynamic characteristics of the battery pack through finite element method (FEM) for safety concerns. However, because of the complication of structure and the number of parts in a battery pack, it is impractical to develop an accurate FEM model. Thus, simplified methods are always applied for modeling. Because battery modules are the most complicated parts and make up the majority of proportion in a battery pack, it is the key to simplification. Using multibody models, this research proposes a simplified method for soft‐connected battery modules, which can be applied to the battery pack FEM model, accurately calculate the dynamic characteristics of a battery pack, and use less computing resources compared with traditional simplified methods. A practical battery pack structure is modeled using this method. Compared with the traditional ones, this method reduces 90% nodes and 97% meshes, excluding the influence of battery pack enclosure, and consumes 40% less memory during calculation. This method also has higher computing efficiency for larger battery packs with more battery modules. The simulation results are well matched with experimental results, which indicate the universality of the simplified model. [ABSTRACT FROM AUTHOR]

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]

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]

Summary: By year 2020, due to enormous growth of production of electric vehicles, it is estimated that approximately 250 000 tons of battery must be disposed or recycled. Till date, the technology to recycle this much amount of batteries in a single year does not exist. Nor, do the methods for recycling are standardized and regulated because of differences in configurations of battery packs. This article conducts a systematic review on research of recycling methods for battery pack used in various stages such as from the dismantling/ disassembly of the battery pack, the detection of the residual energy of the battery, and the recycling/recovery of materials from the battery. The review summarizes basically the 2 main aspects of recycling of battery pack: the mechanical procedure and the chemical recycling. The work describes the existing recycling technology in these 2 aspects and identifies the important research problems in the process of recycling of battery pack such as (1) complexity of dismantling process of battery pack; (2) diversity of connectors used in battery pack; (3) safety of dismantling of battery pack; (4) instability of chemical materials in battery; (5) the chaos of the recycling market; and (6) emerging battery dismantling technologies. One important direction suggested is the automation of battery pack disassembly, which is a main factor towards formulation of generic framework for recycling of battery pack in an efficient manner. Based on these gaps, the present work also proposes a framework for the recycling of battery pack by combining the semi‐automation mechanical procedure of battery pack and enhanced chemical recycling of battery for recovery of vital materials. Future work for authors is to work on establishing and validation of proposed framework. The advantages of the proposed framework are compared with that obtained from the existing framework. The proposed framework when used shall result in efficient and effective recycling of battery module and promote greener environment. [ABSTRACT FROM AUTHOR]

Rechargeable battery industry will see significant growth in the use of battery systems for portable devices and power electronics, renewable energy storage, power systems for transportation, and telecom backup power applications. Despite such promising market sentiment, the battery system management remains as a challenging issue to be resolved in order to provide a safe and reliable power and energy storage system. Here we report advancement in the battery management approach by providing a solution to analyze battery performance variations in a lot of batteries produced from the same manufacturing process. A lot of 100 Li-ion cells were analyzed in order to quantify the inherent cell variations associated with cell manufacturing process and test protocol. Both statistical and electrochemical analyses were used to characterize and quantify the capacity variations among the cells along with other parameters that can be readily derived from the test results. Information extracted from a minimal testing of the cells in the lot and more intensive characterizations on a few cells including one as the nominal sample cell allows the establishment of a single cell model (SCM), based on a generic equivalent circuit, with high accuracy in predicting cell performance. The analyses also permit a carefully crafted logic development of how to separate the origins that cause the cell variations in performance. Such separation of the attributes enable a proper tuning of the cell parameters in the model, which allows the accommodation of cell variations in a battery pack model to handle most of the imbalance issues. A careful validation of the SCM to predict performance of any arbitrary cell in the lot with high accuracy was demonstrated. Copyright © 2009 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]