Advancing state estimation for lithium-ion batteries with hysteresis: systematic extended Kalman filter tuning

Knowledge of remaining battery charge is fundamental to electric vehicle deployment. Accurate measurements of state-of-charge (SOC) cannot be directly obtained, and estimation methods must be used instead. This requires both a good model of a battery and a well-designed state estimator. Here, hysteretic reduced-order battery models and adaptive extended Kalman filter estimators are shown to be highly effective, accurate SOC estimators. A battery model parameterisation framework is proposed, which enhances standardised methods to capture hysteresis effects. The hysteretic model is parameterised for three independent NMC811 lithium-ion cells and is shown to reduce voltage RMS error by 50% across 18-hour automotive drive-cycles. Parameterised models are used alongside an extended Kalman filter, which demonstrates the value of adaptive filter parameterisation schemes. When used alongside an extended Kalman filter, adaptive covariance matrices yield highly accurate SOC estimates, reducing SOC estimation error by 85%, compared to the industry standard battery model.Comment: 22 pages, 8 figures. Journal submissio

A system for determining Li-ion cell cooling coefficients

Current battery data sheets focus on battery energy and power density, neglecting thermal performance. This leads to reduced system level efficiency since cells with poor thermal performance require larger, heavier cooling systems to maintain cell temperatures in a suitable range. To address this a new metric, the Cell Cooling Coefficient (CCC), has been developed and it’s use as a tool for appropriate cell selection has been demonstrated. It also allows the pack designer to calculate which cooling direction method is most suitable by comparing CCC values for tab and surface cooling. The metric is the ratio between the heat rejected from the cell and the temperature difference between the hottest and coolest point. It therefore has units WK−1 and allows a pack designer to easily calculate the required amount of cooling power for the cell given a maximum acceptable temperature rise. In this paper we describe a system and method for the accurate determination of the CCC with the aim of facilitating wider adoption of the metric. The system is able to reliably quantify the surface and tab cooling CCC of any pouch cell

Novel Methods for Measuring the Thermal Diffusivity and the Thermal Conductivity of a Lithium-Ion Battery

Thermal conductivity is a fundamental parameter in every battery pack model. It allows for the calculation of internal temperature gradients which affect cell safety and cell degradation. The accuracy of the measurement for thermal conductivity is directly proportional to the accuracy of any thermal calculation. Currently the battery industry uses archaic methods for measuring this property which have errors up to 50 %. This includes the constituent material approach, the Searle’s bar method, laser/Xeon flash and the transient plane source method. In this paper we detail three novel methods for measuring both the thermal conductivity and the thermal diffusivity to within 5.6 %. These have been specifically designed for bodies like lithium-ion batteries which are encased in a thermally conductive material. The novelty in these methods comes from maintaining a symmetrical thermal boundary condition about the middle of the cell. By using symmetric boundary conditions, the thermal pathway around the cell casing can be significantly reduced, leading to improved measurement accuracy. These novel methods represent the future for thermal characterisation of lithium-ion batteries. Continuing to use flawed measurement methods will only diminish the performance of battery packs and slow the rate of decarbonisation in the transport sector

Towards Optimised Cell Design of Thin Film Silicon-Based Solid-State Batteries via Modelling and Experimental Characterisation

To realise the promise of solid-state batteries, negative electrode materials exhibiting large volumetric expansions, such as Li and Si, must be used. These volume changes can cause significant mechanical stresses and strains that affect cell performance and durability, however their role and nature in SSBs are poorly understood. Here, a 2D electro-chemo-mechanical model is constructed and experimentally validated using steady-state, transient and pulsed electrochemical methods. The model geometry is taken as a representative cross-section of a non-porous, thin-film solid-state battery with an amorphous Si (a-Si) negative electrode, lithium phosphorous oxynitride (LiPON) solid electrolyte and LiCoO2 (LCO) positive electrode. A viscoplastic model is used to predict the build-up of strains and plastic deformation of a-Si as a result of (de)lithiation during cycling. A suite of electrochemical tests, including electrochemical impedance spectroscopy, the galvanostatic intermittent titration technique and hybrid pulse power characterisation are carried out to establish key parameters for model validation. The validated model is used to explore the peak interfacial (a-Si∣LiPON) stress and strain as a function of the relative electrode thickness (up to a factor of 4), revealing a peak volumetric expansion from 69% to 104% during cycling at 1C. The validation of this electro-chemo-mechanical model under load and pulsed operating conditions will aid in the cell design and optimisation of solid-state battery technologies

Lithium-ion battery second life:pathways, challenges and outlook

Net zero targets have resulted in a drive to decarbonise the transport sector worldwide through electrification. This has, in turn, led to an exponentially growing battery market and, conversely, increasing attention on how we can reduce the environmental impact of batteries and promote a more efficient circular economy to achieve real net zero. As these batteries reach the end of their first life, challenges arise as to how to collect and process them, in order to maximise their economical use before finally being recycled. Despite the growing body of work around this topic, the decision-making process on which pathways batteries could take is not yet well understood, and clear policies and standards to support implementation of processes and infrastructure are still lacking. Requirements and challenges behind recycling and second life applications are complex and continue being defined in industry and academia. Both pathways rely on cell collection, selection and processing, and are confronted with the complexities of pack disassembly, as well as a diversity of cell chemistries, state-of-health, size, and form factor. There are several opportunities to address these barriers, such as standardisation of battery design and reviewing the criteria for a battery’s end-of-life. These revisions could potentially improve the overall sustainability of batteries, but may require policies to drive such transformation across the industry. The influence of policies in triggering a pattern of behaviour that favours one pathway over another are examined and suggestions are made for policy amendments that could support a second life pipeline, while encouraging the development of an efficient recycling industry. This review explains the different pathways that end-of-life EV batteries could follow, either immediate recycling or service in one of a variety of second life applications, before eventual recycling. The challenges and barriers to each pathway are discussed, taking into account their relative environmental and economic feasibility and competing advantages and disadvantages of each. The review identifies key areas where processes need to be simplified and decision criteria clearly defined, so that optimal pathways can be rapidly determined for each end-of-life battery

Effectiveness of a national quality improvement programme to improve survival after emergency abdominal surgery (EPOCH): a stepped-wedge cluster-randomised trial

Background: Emergency abdominal surgery is associated with poor patient outcomes. We studied the effectiveness of a national quality improvement (QI) programme to implement a care pathway to improve survival for these patients. Methods: We did a stepped-wedge cluster-randomised trial of patients aged 40 years or older undergoing emergency open major abdominal surgery. Eligible UK National Health Service (NHS) hospitals (those that had an emergency general surgical service, a substantial volume of emergency abdominal surgery cases, and contributed data to the National Emergency Laparotomy Audit) were organised into 15 geographical clusters and commenced the QI programme in a random order, based on a computer-generated random sequence, over an 85-week period with one geographical cluster commencing the intervention every 5 weeks from the second to the 16th time period. Patients were masked to the study group, but it was not possible to mask hospital staff or investigators. The primary outcome measure was mortality within 90 days of surgery. Analyses were done on an intention-to-treat basis. This study is registered with the ISRCTN registry, number ISRCTN80682973. Findings: Treatment took place between March 3, 2014, and Oct 19, 2015. 22 754 patients were assessed for elegibility. Of 15 873 eligible patients from 93 NHS hospitals, primary outcome data were analysed for 8482 patients in the usual care group and 7374 in the QI group. Eight patients in the usual care group and nine patients in the QI group were not included in the analysis because of missing primary outcome data. The primary outcome of 90-day mortality occurred in 1210 (16%) patients in the QI group compared with 1393 (16%) patients in the usual care group (HR 1·11, 0·96–1·28). Interpretation: No survival benefit was observed from this QI programme to implement a care pathway for patients undergoing emergency abdominal surgery. Future QI programmes should ensure that teams have both the time and resources needed to improve patient care. Funding: National Institute for Health Research Health Services and Delivery Research Programme