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The thermal swelling of rechargeable lithium-ion battery cells is investigated as a function of the charge state and the charge/discharge rate. The thermal swelling shows significant dependency on the state of charge and the charge rate. The thermal swelling follows a quadratic form at low temperatures, and shows linear characteristics with respect to temperature at high temperatures in free-swelling conditions. Moreover, the equivalent coefficient of thermal expansion is much larger than that of each electrode and host materials, suggesting that the separator and the complex shape of the cell play a critical role in thermal expansion. Based on the experimental characterization, a novel thermal swelling model is proposed. The model introduces an equivalent coefficient of thermal expansion for the cell and also considers the temperature distribution throughout the battery by using heat transfer theory. The comparison between the proposed model and experiments demonstrates that the model accurately predicts thermal swelling at a variety of charge/discharge rates during operation and relaxation periods. The © 2015. This manuscript version is made available under the Elsevier user license http://www.elsevier.com/open-access/userlicense/1.0/ model is relatively simple yet very accurate. Hence, it can be useful for battery management applied to prolong the cycle life of cells and packs. Keywords Lithium-ion battery; phase transition; swelling; thermal expansion; the coefficient of thermal expansion 1. Introduction Concerns for energy security, instability in world oil markets, and limitations of carbon emissions have accelerated the development of eco-friendly, high-efficiency automobiles. This drives automobile industries toward the development of vehicle electrification technology.Electrified vehicles currently use lithium-ion (Li-ion) batteries as the reversible power source.Li-ion batteries have advantages such as high power/energy density, high potential, and low selfdischarge rate. They are also environmentally friendly and have a long life cycle [1][2][3].While vehicle electrification with the advent of the Li-ion batteries [4] enhances fuel efficiency and reduces CO 2 emissions, many challenges still exist when using Li-ion batteries such as their limited performance at low temperatures [5] and their thermal runaway [6]. Especially, extensive research on vehicle electrification has been driven by stringent safety standards for air and ground applications. Therefore, recent research focuses on the thermal distribution and the heat dissipation of Li-ion battery packs [7,8] as elevated temperatures not only can cause thermal runaway but can also degrade battery life. A variety of heat transfer models have been created

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Three phenomenological force and swelling models are developed to predict mechanical phenomena caused by Li-ion intercalation: a 1-D force model, a 1 st order relaxation model, and a 3-D swelling model. The 1-D force model can estimate the Li-ion intercalation induced force for actual pack conditions with preloads. The model incorporates a nonlinear elastic stiffness to capture the mechanical consequences of Li-ion intercalation swelling. The model also separates the entire state of charge range into three regions considering phase transitions. The 1 st order relaxation model predicts dynamic swelling during relaxation periods. A coefficient of relaxation is estimated from dynamic and quasi-static swelling at operational conditions. The 3-D swelling model predicts the swelling shape on the battery surface for all states of charge. This model introduces an equivalent modulus of elasticity, which is dependent on the state of charge, to

The drone‐based inspection process on power transmission lines needs to be automated due to the large scale of power facilities and the limited line of sight available to drone pilots. Through the task environment analysis, however, it was found that the steel tower structure and energized AC power conductors may cause GPS signal distortion and magnetic interference with a drone's geomagnetic sensor, respectively. These factors could seriously affect the drone's autopilot flight, at worst leading to a crash. To enable drone inspections to be performed in a safe and efficient manner, this paper presents the entire process of operating an autopilot inspection drone on the basis of GPS and GIS information in a hazardous ultrahigh voltage environment, and its application results in the field. This process includes how to measure GPS co‐ordinates of steel towers and how to generate an autopilot flight path. More specifically, the paper examines the potential problems that may occur when drones are applied to areas located in mountains and rivers where humans cannot inspect power lines due to a lack of accessibility, and proposes effective solutions to these practical issues.