In the recent years, lithium-ion batteries have become the battery technology of choice for portable devices, electric vehicles and grid storage. While increasing numbers of car manufacturers are introducing electrified models into their offering, range anxiety and the length of time required to recharge the batteries are still a common concern. The high currents needed to accelerate the charging process have been known to reduce energy efficiency and cause accelerated capacity and power fade. Fast charging is a multiscale problem, therefore insights from atomic to system level are required to understand and improve fast charging performance. The present paper reviews the literature on the physical phenomena that limit battery charging speeds, the degradation mechanisms that commonly result from charging at high currents, and the approaches that have been proposed to address these issues. Special attention is paid to low temperature charging. Alternative fast charging protocols are presented and critically assessed. Safety implications are explored, including the potential influence of fast charging on thermal runaway characteristics. Finally, knowledge gaps are identified and recommendations are made for the direction of future research. The need to develop reliable onboard methods to detect lithium plating and mechanical degradation is highlighted. Robust model-based charging optimisation strategies are identified as key to enabling fast charging in all conditions. Thermal management strategies to both cool batteries during charging and preheat them in cold weather are acknowledged as critical, with a particular focus on techniques capable of achieving high speeds and good temperature homogeneities.

Lithium-ion battery fast charging: A review

This paper presents an overview on charging strategies for lithium-ion batteries. Moreover, a detailed assessment of charging strategies is performed, based on an extensive experimental study with three different cell types. The experimental results reveal that the impact of charging currents and charging voltages on cycle life can vary markedly among different lithium-ion batteries. In general, the cycle life is influenced more by high charging currents than by high discharging currents. Different boost charging protocols have disclosed that high charging currents can deteriorate cycle life not only at high state of charge (SoC), but also at very low SoC. Our investigations on pulse charging show that lithium-ion cells withstand charging pulses of high current or high voltage without any deterioration in cycle life, when the duration of the pulses remains short and the mean current and voltage values are considerably lower. For pulses of less than 1 s, cycle life has been similar for pulsed and continuous charging with the same mean charging currents and identical cycle depths. This paper also presents the impact of charging currents and charging voltages on capacity utilization, charging time, and efficiency to support the development process of optimized charging protocols for practical applications.

Charging protocols for lithium-ion batteries and their impact on cycle life—An experimental study with different 18650 high-power cells

Application of electrochemical impedance spectroscopy to commercial Li-ion cells: a review

Fast and safe charging protocols are crucial for enhancing the practicality of batteries, especially for mobile applications, such as smartphones and electric vehicles. This paper proposes an innovative approach to devising optimally health-conscious fast-safe charge protocols. A multiobjective optimal control problem is mathematically formulated via a coupled electro-thermal-aging battery model, where electrical and aging submodels depend upon the core temperature captured by a two-state thermal submodel. The Legendre–Gauss–Radau pseudospectral method with adaptive multi-mesh-interval collocation is employed to solve the resulting highly nonlinear six-state optimal control problem. Charge time and health degradation are, therefore, optimally traded off, subject to both electrical and thermal constraints. Minimum-time, minimum-aging, and balanced charge scenarios are examined in detail. Sensitivities to the upper voltage bound, ambient temperature, and cooling convection resistance are investigated as well. Experimental results are provided to compare the tradeoffs between a balanced and traditional charge protocol.

Optimal Charging of Li-Ion Batteries With Coupled Electro-Thermal-Aging Dynamics

Concept of reliability and safety assessment of lithium-ion batteries in electric vehicles: Basics, progress, and challenges

Li-ion batteries are widely used in industrial applications due to their high energy density, slow material degradation, and low self-discharge The existing advanced battery management systems (ABMs) in industry employ semiempirical battery models that do not use first-principles understanding to relate battery operation to the relevant physical constraints, which results in conservative battery charging protocols This article proposes a Quadratic Dynamic Matrix Control (QDMC) approach to minimize the charge time of batteries to reach a desired state of charge (SOC) while taking temperature and voltage constraints into account This algorithm is based on an input-output model constructed from a first-principles electrochemical battery model known in the literature as the pseudo two-dimensional (P2D) model In simulations, this approach is shown to significantly reduce charging time

Real-time model predictive control for the optimal charging of a lithium-ion battery

Identification of Lithium Plating in Lithium-Ion Batteries using Nonlinear Frequency Response Analysis (NFRA)

Nonlinear Frequency Response Analysis (NFRA) of Lithium-Ion Batteries

Nonlinear Frequency Response Analysis on Lithium-Ion Batteries: A Model-Based Assessment

In this study, we show an effective data-driven identification of the State-of-Health of Lithium-ion batteries by Nonlinear Frequency Response Analysis. A degradation model based on support vector regression is derived from highly informative Nonlinear Frequency Response Analysis data sets. First, an ageing test of a Lithium-ion battery at 25 °C is presented and the impact of relevant ageing mechanisms on the nonlinear dynamics of the cells is analysed. A correlation measure is used to identify the most sensitive frequency range for ageing tests. Here, the mid-frequency range from 1 Hz to 100 Hz shows the strongest correlation to Lithium-ion battery degradation. The focus on the mid-frequency range leads to a dramatic reduction in measurement time of up to 92% compared to standard measurement protocols. Next, informative features are extracted and used to parametrise the support vector regression model for the State of Health degradation. The performance of the degradation model is validated with additional cells and validation data sets, respectively. We show that the degradation model accurately predicts the State of Health values. Validation data demonstrate the usefulness of the Nonlinear Frequency Response Analysis as an effective and fast State of Health identification method and as a versatile tool in the diagnosis of ageing of Lithium-ion batteries in general.

Nicolas Wolff

Papers

Real-time model predictive control for the optimal charging of a lithium-ion battery

Identification of Lithium Plating in Lithium-Ion Batteries using Nonlinear Frequency Response Analysis (NFRA)

Nonlinear Frequency Response Analysis (NFRA) of Lithium-Ion Batteries

Nonlinear Frequency Response Analysis on Lithium-Ion Batteries: A Model-Based Assessment

State-of-Health Identification of Lithium-Ion Batteries Based on Nonlinear Frequency Response Analysis: First Steps with Machine Learning