International audienceSafety issues pertaining to Li-ion batteries justify intensive testing all along their value chain. However, progress in scientific knowledge regarding lithium based battery failure modes, as well as remarkable technologic breakthroughs in computing science, now allow for development and use of prediction tools to assist designers in developing safer batteries. Subsequently, this paper offers a review of significant modeling works performed in the area with a focus on the characterization of the thermal runaway hazard and their relating triggering events. Progress made in models aiming at integrating battery ageing effect and related physics is also discussed, as well as the strong interaction with modeling-focused use of testing, and the main achievements obtained towards marketing safer systems. Current limitations and new challenges or opportunities that are expected to shape future modeling activity are also put in perspective. According to market trends, it is anticipated that safety may still act as a restraint in the search for acceptable compromise with overall performance and cost of lithium-ion based and post lithium-ion rechargeable batteries of the future. In that context, high-throughput prediction tools capable of screening adequate new components properties allowing access to both functional and safety related aspects are highly desirable

ln this paper an empirical capacity fade model for Li-ion batteries has been developed, calibrated and validated for a NCA/C and a LFP/C Li-ion cell. Based on extensive experimental work, it is able to describe both cycle and calendar effects on aging. The stress factors taken into account for each aging mode are the state of charge and the tempe rature for calendar aging, and the temperature and the current for cycle aging. A simple approach has been adopted in order to instantaneously apply either cycle aging or calendar aging according to operating conditions and th us accurately mode! aging effects due to dynamic operating conditions. This model has then been coupled to an electrothermal mode l and integrated in a system simulation software application in order to assess the effect of charging strategies and V2G on battery lifetime. When compared, LFP/C and NCA/C exhibited different behaviors when submitted to V2G scenarios. Light V2G scenarios led to a low aging for LFP/C based battery but tended to slightly increase the aging of NCA/C based battery according to simulations.

Li-ion secondary rechargeable batteries are becoming the preferred solution to store energy on board of new generation electric and hybrid vehicles or manage renewable energy in stationary applications. However, Li-ion batteries (LIBs) are still suffering limited lifetime, high cost and significant safety issues increasing their time to mass market. Thermal runaway is still nowadays considered as a major hazard of LIBs. This multiscale and multistep phenomenon originating at the microscale level potentially leads to uncontrolled fire and explosion of the battery. This work is focused on the development and validation of a 3D physical model of the LIB electro-thermal behavior nearby thermal runaway conditions. A combined modeling and experimental investigation provides a better understanding of the mechanisms leading to thermal runaway of LIBs, and of the ageing influence on this process. One major outcome of this work is also the proven fact that calendar ageing leads to a delayed onset of the cell self-heating temperature with a thermal runaway starting at a lower temperature. This is supported by computer simulations showing that the thickening of the solid electrolyte interface (SEI) hinders the diffusion of Li ions, which delays the degradation of the negative electrode and the occurrence of thermal runaway. HIGHLIGHTS  Development of an original 3D thermal runaway model including calendar ageing.  Model includes 3D thermal, 3D chemical reaction, and 0D calendar ageing sub-models. Calibration of the model for cylindrical 26650 LFP/C cells using a BTC. Validation of the model for fresh as well as 10% and 30% aged cells in oven tests.  Fresh and aged cells are compared in terms of critical temperatures under overheating 2

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This paper presents a simulation study dealing with the influence of different factors on the energy consumption of an electric vehicle (EV). Due to the limited quantity of energy embedded in the battery, EVs are very sensitive to parameters which can influence their energy consumption and then can induce huge variations in their actual range. Among all these factors, driving conditions, auxiliaries' impact, driver's aggressiveness and braking energy recovery strategy are to be considered as the main factors influencing the EV energy consumption. The objective of this paper is thus to simulate and quantify the influence of each factor independently. For this, a virtual EV simulator has been created and validated through EVs experiments on a climatic 4WD chassis dyno in the frame of a project sponsored by the French ADEME and with the help of PSA, Renault and Tazzari car manufacturers. This simulator, validated thanks to a limited number of experimental results, has been then used on a very large range of operating conditions and hypotheses to extrapolate experimental results and help the analyses of influencing factors.