State of Health Estimation of Lithium‐Ion Batteries in Electric Vehicles under Dynamic Load Conditions

Among numerous functions performed by the battery management system (BMS), online estimation of the state of health (SOH) is an essential and challenging task to be accomplished periodically. In electric vehicle (EV) applications, accurate SOH estimation minimizes failure risk and improves reliability by predicting battery health conditions. The challenge of accurate estimation of SOH is based on the uncertain dynamic operating condition of the EVs and the complex nonlinear electrochemical characteristics exhibited by the lithium‐ion battery. This paper presents an artificial neural network (ANN) classifier experimentally validated for the SOH estimation of lithium‐ion batteries. The ANN‐based classifier model is trained experimentally at room temperature under dynamic variable load conditions. Based on SOH characterization, the training is done using features such as the relative values of voltage, state of charge (SOC), state of energy (SOE) across a buffer, and the instantaneous states of SOC and SOE. At implementation, due to the slow dynamics of SOH, the algorithm is triggered on a large‐scale periodicity to extract these features into buffers. The features are then applied as input to the trained model for SOH estimation. The classifier is validated experimentally under dynamic varying load, constant load, and step load conditions. The model accuracies for validation data are 96.2%, 96.6%, and 93.8% for the respective load conditions. It is further demonstrated that the model can be applied on multiple cell types of similar specifications with an accuracy of about 96.7%. The performance of the model analyzed with the confusion matrices is consistent with the requirements of the automotive industry. The classifier was tested on a Texas F28379D microcontroller unit (MCU) board. The result shows that an average real‐time execution speed of 8.34 μs is possible with a negligible memory occupation

Effect of forced carbonation on the behaviour of a magnesia-stabilised clay soil

This is the author accepted manuscript. The final version is available from Routledge via the DOI in this recordThis paper presents an investigation into the behaviour of a clay soil stabilised with MgO under forced carbonation and comparison with conventional chemical stabilisation methods. The tests were conducted in two groups. In the first group the soil was mixed with 5, 10, 15 and 20% MgO or cement. Unconfined compressive strength (UCS) tests were performed on compacted samples from these mixtures at curing times of 7, 14 and 28 days. In the second group, samples prepared with different percents of MgO were subjected to CO2 under pressures of 0.5, 1.0 and 1.5 bar for periods of 4, 8, 12 and 24 h. The results showed that adding MgO increases the strength of the soil and, like other binders, the amount of increase in strength depends on the percent of MgO and curing time. It is also resulted that the effect of MgO is less than cement in increasing the strength. It was revealed that forced carbonation can facilitate the stabilisation of MgO-stabilised soil in a few hours compared with usual process that takes several days. XRD and SEM results showed that the gained strength is resulted from the interaction between the soil and the agents

Direct laser deposited titanium with controlled porosity for bone tissue engineering

The potential of engineered porous materials for aiding the osseointegration of metallic dental and orthopedic implants is well established. A range of techniques, such as powder metallurgy, plasma-spraying and titanium fiber meshing have been tried to produce the implant structures with control on porosity and other pertinent characteristics. In the present work, direct laser deposition of pure titanium powder (particle size: -100/+63 microns) was carried out to form porous structure. A 1 kW fiber laser, integrated with lateral powder feed nozzle and workstation, was used at different primary process parameters (laser power, powder mass flow rate, transverse speed, hatch parameter) to fabricate a number of multi-layer structures. The relevant structural parameters of these fabricated structures were studied as a function of the process parameters using various techniques. The result of these studies are presented