The adoption of electric vehicles is expected to soon widespread to cope with energy transition needs; however, concerns on battery lifetime arise, especially related to charging behaviors, vehicle usage habits, vehicle-to-grid and weather conditions. In fact, lifetime battery modeling is a challenging dynamic to characterize, as it involves complex chemical processes related to charging, discharging and temperature dynamics over long time spans that are often difficult to dominate, given the large uncertainties. Having a fatigue-like behavior, the battery aging has sometimes been modeled using rainflow-counting algorithms, yet traditional modeling is not holistic and approximations are used, especially when considering temperature or current dynamics. Based on experimental data, this paper aims at developing a holistic battery degradation model based on rainflow-counting algorithm to properly account for all major determinants of capacity loss, namely cycling usage, calendar lifetime, dynamic temperature and battery current. The approach is coupled with a physical-electro-thermal modeling of the vehicle system, developed in Modelica language, to accurately simulate the intertwined thermal and electrical behavior of the system subject to different usage charging behaviors, including slow and fast charging, as well as vehicle-to-grid application. The proposed case study shows the expected lifetime of electric vehicles to be comparable with of traditional cars (10–20y) and that the proposed temperature-dependent battery modeling enables reducing estimation errors up to 27%. A sensitivity on different climate zones has been considered and results suggest that cool climates can increase life expectancy by 30% with respect to hot climates in typical Italian contexts. 

Battery lifetime of electric vehicles by novel rainflow-counting algorithm with temperature and C-rate dynamics: Effects of fast charging, user habits, vehicle-to-grid and climate zones

Lithium batteries for energy storage systems are a prominent solution for both stationary and mobile applications. Electro-thermal modelling of the cell is a useful tool for monitoring voltage and temperature in order to predict battery behaviour especially in cases of critical operative conditions. This paper provides a modelling approach focusing on the calibration of parameters of an electro-thermal model for large prismatic LFP lithium cells. The designed model is tuned by means of experimental tests that identify a set of parameters that are function of a cell’s state-of-charge and temperature. The model outputs are voltage, cell surface, and internal temperature profiles, which are validated against experimental data referring to realistic working conditions, even providing an intense level of thermal stress. The model accuracy is marked by a voltage mean average error lower than 1% and a mean cell surface temperature deviation lower than 1 K.

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An Electro-Thermal Model for LFP Cells: Calibration Procedure and Validation

Modelling thermal behaviour of battery packs in pure electric vehicles (BEVs) is one of the most demanding tasks in powertrain design activities. The complexity is given by the need of considering several aspects like internal geometry, cooling circuit, etc. for which the standard approach based on equivalent circuit model seems not to be adequate. The aim of this paper is instead to demonstrate how it is possible to maintain the equivalent circuit model approach, by making minimal changes and by using data from vehicle CAN network. Then, the model can be used to correctly achieve battery pack temperature under different realistic use conditions. 

Modelling lithium battery packs from single cell electro-thermal equivalent circuit model

Batteries are critical components of battery electric vehicles (BEVs) and yet their expected lifetime is hard to estimate. Various determinants play a significant role, among which cell temperatures and usage profile are notably the most predominant, but their impact is complex to estimate. The variability of the vehicle usage patterns makes it difficult to estimate typical stresses on the battery, and cell temperatures are often unknown conversely to the ambient temperature, that is usually used in degradation models. For these reasons, in this study we present a methodology for estimating the expected battery lifetime in electric vehicles (EVs) through a comprehensive powertrain, electrical and thermal model of the vehicle and its battery, including a battery degradation model. Supported by experimental measures, the whole model, including the battery cooling system, is calibrated with data obtained from the onboard Controller Area Network (CAN) of a BEV with average error below 1°C. The case study to represent typical traffic conditions on Italian routes highlights that the approach is robust, expected battery lifetimes are suitable for typical vehicle usage, and that appropriate battery thermal modelling can reduce errors in the lifetime assessment of beyond 40-50%. The study emphasizes the importance of active thermal management in preserving battery health, and the methodology provides a foundation for further multi-disciplinary modeling of EV battery aging.

Electro-Thermal Modeling and aging evaluation of Lithium Battery Packs for Electric Vehicles

Modeling lithium-ion batteries is crucial for electrochemical energy storage to characterize their behavior and predict their State-Of-Charge and State-Of-Health. Equivalent Circuit Models can identify voltage and temperature profiles under a given input current with little computational cost. However, they cannot explain relevant microscopic phenomena that determine the battery's capability to deliver power and be efficiently charged. Conversely, Physics-Based Models can consider advanced physics and account for microscopic information at an increased cost, precluding their utilization in Battery Management Systems. This paper proposes to validate and integrate the two cited modelling approaches applied to a commercial lithium iron phosphate battery. The latter are validated with discharge-charge experimental tests, and microstructural data directly measured through the experimental disassembly of the battery. In this way, equivalent battery models become ideally linked to physics-based ones to fit all the internal electrochemical processes for a complete understanding of the evolution of battery states over time. 

Calibration and Validation of Equivalent Circuit and Physics-Based Models for Li-ion Battery

As the use of lithium batteries for energy storage systems is worldwide increasing both for stationary and mobile applications, the possibility to model the batteries electrical and thermal behaviour is fundamental. A complete battery is usually composed by several minor size cells linked together: hence, for a whole battery model, a single cell model is necessary. This paper shows the development of a simplified electro-thermal model for small size lithium cells, able to estimate voltage and temperature with a maximum average error lower than 3% between model and experimental data. The cell electrical and thermal parameters are calibrated through experimental tests performed in University of Pisa laboratories, in collaboration with the company Toyota Material Handling Manufacturing Italy.

Simplified Electro-Thermal Model For Lithium Cells Based On Experimental Tests

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Simplified Electro-Thermal Model For Lithium Cells Based On Experimental Tests