Lifetime and Aging Degradation Prognostics for Lithium-ion Battery Packs Based on a Cell to Pack Method

Aging diagnosis of batteries is essential to ensure that the energy storage systems operate within a safe region. This paper proposes a novel cell to pack health and lifetime prognostics method based on the combination of transferred deep learning and Gaussian process regression. General health indicators are extracted from the partial discharge process. The sequential degradation model of the health indicator is developed based on a deep learning framework and is migrated for the battery pack degradation prediction. The future degraded capacities of both battery pack and each battery cell are probabilistically predicted to provide a comprehensive lifetime prognostic. Besides, only a few separate battery cells in the source domain and early data of battery packs in the target domain are needed for model construction. Experimental results show that the lifetime prediction errors are less than 25 cycles for the battery pack, even with only 50 cycles for model fine-tuning, which can save about 90% time for the aging experiment. Thus, it largely reduces the time and labor for battery pack investigation. The predicted capacity trends of the battery cells connected in the battery pack accurately reflect the actual degradation of each battery cell, which can reveal the weakest cell for maintenance in advance.

Electric bus platform for urban mobility

Today, the technology of automatic battery charging based on Wireless Power Transfer (WPT) for the electric mass transit industry involving electric trains, buses and trams, is being used more and more. The modern solution described in this paper proposes an innovative technology for mixed charging of electric buses, either by wireless charging for 2-3 minutes in selected stations, or by plug-in charging at the end of the bus line, which results in only minimal energy storage on board - practically enough to get to the next charging station. The reduction of the weight of the battery packs determines the increase of the number of passengers transported, but also a reduction of the purchase price of the bus, without reducing the performances. The conversion can cost about half the price of new electric buses, depending on the condition of the vehicle and the extent of the work. This solution can be applied especially for the conversion of Diesel buses into electric buses which is not only sustainable, but also significantly better in terms of investment and operational costs, comparing with the purchase of new electric buses.

Environmental Impact of EV Batteries and Their Recycling

Electrifying transportation is one of the biggest keys to solving the looming climate crisis. The demand for electric vehicles (EV) is booming in the last five years and will increase in the coming years. In this modern age, where EV is the finest means of transportation due to null exhaust gases, there is a dire need to think about ways of recycling and reusing those batteries associated with EVs. In this context, it is estimated that post-vehicle battery packs application will be crossed from 1.4 million to 6.8 million by the year 2035. Numerous researches have been done on the re-purposing and safe disposal of EV batteries. However, presently, Lithium-ion batteries (LiBs) are the optimal choice for electric transportation due to greater energy density, compact size, and extended life cycles. Nonetheless, the trade-off between re-purposing and disposal of LiBs is substantial for the protection of the environment and human health. Regrettably, Lithium-ion battery recycling percentage is only 3% currently whereas its revival is negligible.

Full-scale Fire Suppression Tests to Analyze the Effectiveness of Existing Lithium-ion Battery Fire Response Procedures for Electric Vehicle Fires

The number of registered eco-friendly vehicles has exceeded a million, and their market share has expanded. In this study, the effectiveness of existing fire response procedures for lithium-ion batteries, which are widely used in eco-friendly vehicles, was investigated by using water-based extinguishing agents, fire blankets, and flood barriers. Water, wetting agents, and foaming agents were sprayed on the underside of battery packs. A temperature decrease rate of ~0.08 ℃ was measured, and no significant difference was observed between the extinguishing agents. Continuous thermal runaway occurred when a fire blanket was applied, and the temperature inside the damaged battery pack rapidly decreased after water permeated its cracks. Quantitative analysis of fire suppression methods can provide information toward the development of practical fire incident response plans for electric vehicles.