Dr Paul Henshall

The exponential growth of electric and hybrid vehicles, now numbering close to 6 million on the roads, has highlighted the urgent need to address the environmental impact of their lithium-ion batteries as they approach their end-of-life stages. Repurposing these batteries as second-life batteries (SLBs) for less demanding non-automotive applications is a promising avenue for extending their usefulness and reducing environmental harm. However, the shorter lifespan of SLBs brings them perilously close to their ageing knee, a critical point where further use risks thermal runaway and safety hazards. To mitigate these risks, effective battery management systems must accurately predict the state of health of these batteries. In response to this challenge, this study employs time-series artificial intelligence (AI) models to forecast battery degradation parameters using historical data from their first life cycle. Through rigorous analysis of a lithium-ion NMC cylindrical cell, the study tracks the trends in capacity and internal resistance fade across both the initial and second life stages. Leveraging the insights gained from first-life data, predictive models such as the Holt–Winters method and the nonlinear autoregressive (NAR) neural network are trained to anticipate capacity and internal resistance values during the second life period. These models demonstrate high levels of accuracy, with a maximum error rate of only 2%. Notably, the NAR neural network-based algorithm stands out for its exceptional ability to predict local noise within internal resistance values. These findings hold significant implications for the development of specifically designed battery management systems tailored for second-life batteries.

The increasing number of electric vehicles (EVs) on the roads has led to a rise in the number of batteries reaching the end of their first life. Such batteries, however, still have a capacity of 75–80% remaining, creating an opportunity for a second life in less power-intensive applications. Utilising these second-life batteries (SLBs) requires specific preparation, including grading the batteries based on their State of Health (SoH); repackaging, considering the end-use requirements; and the development of an accurate battery-management system (BMS) based on validated theoretical models. In this paper, we conduct a technical review of mathematical modelling and experimental analyses of SLBs to address existing challenges in BMS development. Our review reveals that most of the recent research focuses on environmental and economic aspects rather than technical challenges. The review suggests the use of equivalent-circuit models with 2RCs and 3RCs, which exhibit good accuracy for estimating the performance of lithium-ion batteries during their second life. Furthermore, electrochemical impedance spectroscopy (EIS) tests provide valuable information about the SLBs’ degradation history and conditions. For addressing calendar-ageing mechanisms, electrochemical models are suggested over empirical models due to their effectiveness and efficiency. Additionally, generating cycle-ageing test profiles based on real application scenarios using synthetic load data is recommended for reliable predictions. Artificial intelligence algorithms show promise in predicting SLB cycle-ageing fading parameters, offering significant time-saving benefits for lab testing. Our study emphasises the importance of focusing on technical challenges to facilitate the effective utilisation of SLBs in stationary applications, such as building energy-storage systems and EV charging stations.

The service life of Lithium-ion batteries disposed from electric vehicles, with an approximate remaining capacity of 75–80%, can be prolonged with their adoption in less demanding second life applications such as buildings. A photovoltaic energy generation system integrated with a second life battery energy storage device is modelled mathematically to assess the design’s technical characteristics. The reviewed studies in the literature assume, during the modelling process, that the second life battery packs are homogeneous in terms of their initial state of health and do not consider the module-to-module variations associated with the state of health differences. This study, therefore, conducts mathematical modelling of second life battery packs with homogenous and heterogeneous state of health in module level using second-order equivalent circuit model (ECM). The developed second-order ECM is validated against experimental data performed in the lab on 3Ah NCM batteries. The degradation parameters are also investigated using the battery cell’s first life degradation data and exponential triple smoothing (ETS) algorithm. The second-order ECM is integrated with the energy generation system to evaluate and compare the performance of the homogenous and heterogeneous battery packs during the year. Results of this study revealed that in heterogeneous packs, a lower electrical current and higher SOC is observed in modules with lower state of health due to their higher ohmic resistance and lower capacity, compared to the other modules for the specific battery pack configuration used in this study. The methodology presented in this study can be used for mathematical modelling of second life battery packs with heterogenous state of health of cells and modules, the simulation results of which can be employed for obtaining the optimum energy management strategy in battery management systems.

Real-time battery modelling advancements have quickly become required as the adoption of battery electric vehicles (BEVs) has rapidly increased. In this paper an open-source, improved discrete realisation algorithm, implemented in Julia for the creation and simulation of reduced-order, real-time capable physics-based models is presented. This work reduces the Doyle–Fuller–Newman electrochemical model into continuous-form transfer functions and introduces a computationally informed discrete realisation algorithm (CI-DRA) to generate the reduced-order representation. Further improvements in conventional offline model creation are obtained as well as achieving in-vehicle capable model creation for ARM-based computing architectures. Furthermore, a parametric sensitivity analysis of the presented architecture is completed as well as experimental validation of a worldwide harmonised light vehicle test procedure (WLTP) for an LG Chem. M50 21700 parameterisation. A performance comparison to a MATLAB implementation is completed showcasing a mean computational time improvement of 3.51 times for LiiBRA.jl on x86 hardware. Finally, an ARM-based implementation showcases full system model generation within three minutes for potential in-vehicle.

This study investigates the design and sizing of the second life battery energy storage system applied to a residential building with an EV charging station. Lithium-ion batteries have an approximate remaining capacity of 75–80% when disposed from Electric Vehicles (EV). Given the increasing demand of EVs, aligned with global net zero targets, and their associated environmental impacts, the service life of these batteries, could be prolonged with their adoption in less demanding second life applications. In this study, a technical assessment of an electric storage system based on second life batteries from electric vehicles (EVs) is conducted for a residential building in the UK, including an EV charging station. The technical and energy performance of the system is evaluated, considering different scenarios and assuming that the EV charging load demand is added to the off-grid photovoltaic (PV) system equipped with energy storage. Furthermore, the Nissan Leaf second life batteries are used as the energy storage system in this study. The proposed off-grid solar driven energy system is modelled and simulated using MATLAB Simulink. The system is simulated on a mid-winter day with minimum solar irradiance and maximum energy demand, as the worst case scenario. A switch for the PV system has been introduced to control the overcharging of the second life battery pack. The results demonstrate that adding the EV charging load to the off-grid system increased the instability of the system. This, however, could be rectified by connecting additional battery packs (with a capacity of 5.850 kWh for each pack) to the system, assuming that increasing the PV installation area is not possible due to physical limitations on site.

Vacuum flat plate (VFP) solar thermal collectors exhibit excellent optical and thermal characteristics due to a combination of wide surface area and high vacuum thermal insulation offering a high performance and architecturally versatile collector with a variety of applications for industrial process heat and building integration. A vacuum flat plate solar collector consists of a solar absorber in a flat vacuum enclosure comprising glass or glass and metal covers sealed around the periphery with an array of support pillars to maintain the separation of the enclosure under atmospheric pressure. The edge seal must be both mechanically strong and hermetic to ensure the durability of the internal vacuum over collector lifetime. This presents several challenges for the fabrication of flat vacuum enclosures. In this study a novel sealing technique is presented using a tin-based alloy, Cerasolzer 217, to create the vacuum seal between two glass panes and an edge separating spacer. The sealing process is undertaken at temperatures ≤250 °C allowing the use of thermally tempered glass panes. The mechanical strength of the edge seal was investigated using a tensometer. It was demonstrated that the bond between glass and edge spacer was sufficiently strong to withstand induced stresses in the edge seal region. The edge seal was leak tested using a conventional Helium mass spectrometer leak detector and was shown to possess leak rates low enough to maintain an adequate vacuum pressure to supress conductive and convective heat transfer in the collector. A finite element method (FEM) is developed and validated against the experimental results and employed to predict the stresses in different regions of the enclosure. It was found that the mechanical strength limits of the seal and glass are higher than the stresses in the edge seal region and on the glass surface, respectively.

The global market trend for Vacuum Insulation Panels (VIPs) is projecting a significant increase in their uptake in the construction sector. This is mainly due to the uniquely high-performance properties of the ultra-thin insulation materials. This uptake, however, can potentially be hindered by the VIPs’ higher cost and environmental impacts when compared with conventional insulation materials. This paper, for the first time, presents a detailed evaluation of the environmental impact of the most common type of VIPs currently used in different applications with a focus on alternating the core material as the main contributing component to their footprint. Pyrogenic silica, glass fibre, expanded polystyrene, aerogel and a silica/sawdust hybrid core were analysed from cradle to gate. The study, on a comparative basis, demonstrates the sensitivity of the various environmental impact categories to the internal vacuum pressure and the subsequent thermal conductivity values. The results show a lower environmental impact for glass fibre and low density expanded polystyrene compared to the other alternatives. Pyrogenic silica, the most common core material, had the highest environmental impact out of the core materials considered. The higher environmental impacts of pyrogenic silica suggest that measures such as the recycling of the core material alongside the deployment of eco-friendlier manufacturing techniques should be considered if the material is to compete environmentally with the other alternative materials.

A primary drawback of solar thermal technologies, especially in a domestic setting, is that collection of thermal energy occurs when solar irradiance is abundant and there is generally little requirement for heating. Thermochemical Energy Storage (TCES) offers a means of storing thermal energy interseasonally with little heat loss. A combination of a Solar Thermal Collector (STC) and TCES system will allow a variety of different heating applications, such as domestic space and hot water heating as well as low temperature industrial process heat applications to be met in a low carbon way. This paper describes and assesses the feasibility of two novel technologies currently under development at Loughborough University; i) an evacuated flat plate STC and ii) composite TCES materials, coupled together into a system designed to store and supply thermal energy on demand throughout the year. Experimental results of composite TCES materials along with predicted performance of STC's are used within a developed model to assess key metrics of conceptual TCES + STC systems feasibility, including; charging time, payback time, cost/kWh, energy savings and CO2 savings. This paper demonstrates the economic, energy and carbon savings potential of conceptual TCES + STC systems suitable for domestic use.

Heat losses from a flat panel solar collector can be significantly reduced by lowering the internal pressure to

Non-concentrating solar thermal collectors are generally available in two forms, flat plate or evacuated tube. Recently a third configuration, the evacuated flat plate, has attracted interest due to enhanced performance and aesthetic characteristics. By isolating a solar absorber in a vacuum space (

Creating a vacuum (