Current road transport heavily relying on fossil fuels has caused severe public concerns about energy affordability, air quality, and environmental friendliness. In the foreseeable future, the only possible way to dispel these concerns is via the electrification of vehicle powertrains integrated with renewable and sustainable energy. Fulfilling such a fossil-fuel-free vision greatly depends on the continued advancement of battery technology, which is still the most expensive and perhaps the least understood vehicle component. Although having been recognised as today’s leading commercial energy storage source among various cell chemistries, lithium-ion (Li-ion) battery represents a limiting factor in energy density, “refuelling” time, and cycle life, compared to fossil fuels burned in internal combustion engines. Despite this, available battery systems are compromised even further with conservative designs, with 20-50% underutilised energy capacity, or aggressive de-rating, in order to present safety issues and premature ageing. This in turn considerably reduces the cost-benefit of the battery systems. One way to improve the cost-benefit is through better understanding leading to less conservative safety factors enabled by advanced management systems for safe and optimal use of Li-ion batteries.
The fast charging problem can be roughly described as determining appropriately applied current, which recharges a battery from an initial state of charge (SOC) to a predefined SOC level in the shortest time but does not cause dangerous events like thermal runaway and does not excessively degrade the battery state of health (SOH). In this process, battery electrochemical, thermal, and ageing dynamics will simultaneously evolve and interact with each other over multiple timescales and length scales. The corresponding mathematical structure is overly complicated and in fact, there is no individual model in the literature that is capable of accurately capturing all characteristics of a battery over its lifetime for practical implementation. The lack of accurate prediction battery models for practical use forms one of the biggest technical challenges in the field of advanced charging management. In addition, none of the internal battery states is measurable in onboard vehicle applications through currently available in-situ sensing techniques. This means, to real-time monitor and control a battery’s distributed behaviour associated with chemical reactions and diffusion, one has to develop estimation techniques in the presence of limited and noisy measurements, which are current, voltage, and temperature, at best. Third, as large current rates will be included in the fast charge process, dangers can be easily triggered if the management strategies are not designed meticulously and appropriately. How to always maintain an acceptable safety and health margin while archiving optimal performance is another big challenge that was focused in this project.
