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Showing papers by "Land Rover published in 2017"


Journal ArticleDOI
TL;DR: In this paper, the impact of compressive pressure on battery degradation was studied in automotive battery modules/packs by way of rigid cell housing within the modules, and the authors identified the evolution of the compressive pressures over multiple cycles, showing that pressure increases with cycling.
Abstract: In application, lithium-ion pouch-format cells undergo expansion during cycling. To prevent contact loss between battery pack components and delamination and deformation during battery operation, compressive pressure is applied to cells in automotive battery modules/packs by way of rigid cell housing within the modules. In this paper, the impact of such compressive pressure on battery degradation is studied. Samples of commercial, 15 Ah LiNiMnCoO2/Graphite electrode pouch-type cells were cycled 1200 times under atmospheric, 5 psi and 15 psi compressive loads. After 1200 cycles, the capacity fade for 0, 5 and 15 psi loads was11.0%, 8.8% and 8.4%, respectively; the corresponding power fade was found to be 7.5%, 39% and 18%, respectively, indicating power fade peaks between 0 and 15psi. This contrasting behaviour is related to the wettability increase and separator creep within the cell after compressive load is applied. The opposing capacity fade and power fade results require consideration from automotive battery engineers at the design stage of modules and packs. In addition to capacity fade and power fade results, the study identified the evolution of compressive pressures over multiple cycles, showing that pressure increases with cycling.

57 citations


Journal ArticleDOI
TL;DR: This work investigates the effect on the battery of removing 99.1% of the total stored energy following periods of calendar ageing at low voltages, at and well below the manufacturer’s recommended value.
Abstract: In freight classification, lithium-ion batteries are classed as dangerous goods and are therefore subject to stringent regulations and guidelines for certification for safe transport. One such guideline is the requirement for batteries to be at a state of charge of 30%. Under such conditions, a significant amount of the battery’s energy is stored; in the event of mismanagement, or indeed an airside incident, this energy can lead to ignition and a fire. In this work, we investigate the effect on the battery of removing 99.1% of the total stored energy. The performance of 8Ah C6/LiFePO4 pouch cells were measured following periods of calendar ageing at low voltages, at and well below the manufacturer’s recommended value. Battery degradation was monitored using impedance spectroscopy and capacity tests; the results show that the cells stored at 2.3 V exhibited no change in cell capacity after 90 days; resistance rise was negligible. Energy-dispersive X-ray spectroscopy results indicate that there was no significant copper dissolution. To test the safety of the batteries at low voltages, external short-circuit tests were performed on the cells. While the cells discharged to 2.3 V only exhibited a surface temperature rise of 6 °C, cells at higher voltages exhibited sparks, fumes and fire.

18 citations


Journal ArticleDOI
TL;DR: This paper presents the Warwick-JLR Driver Monitoring Dataset (DMD) and analyse it to investigate the feasibility of using vehicle telemetry data for determining the driver workload, and performs a statistical analysis of subjective ratings, physiological data, and vehicletelemetry data collected during a track study.
Abstract: Driving is a safety critical task that requires a high level of attention and workload from the driver. Despite this, people often also perform secondary tasks such as eating or using a mobile phone, which increase workload levels and divert cognitive and physical attention from the primary task of driving. If a vehicle is aware that the driver is currently under high workload, the vehicle functionality can be changed in order to minimize any further demand. Traditionally, workload measurements have been performed using intrusive means such as physiological sensors. Another approach may be to use vehicle telemetry data as a performance measure for workload. In this paper, we present the Warwick-JLR Driver Monitoring Dataset (DMD) and analyse it to investigate the feasibility of using vehicle telemetry data for determining the driver workload. We perform a statistical analysis of subjective ratings, physiological data, and vehicle telemetry data collected during a track study. A data mining methodology is then presented to build predictive models using this data, for the driver workload monitoring problem.

2 citations