Advanced battery diagnostics are key to understanding battery state and residual value for second-life applications. At Coventry University we are developing advanced diagnostic methods based on impedance spectroscopy and embedded sensors. This allows for rapid assessment of batteries as compared to conventional methods such as capacity measurement. Here we also present our work done in collaboration with LEVC under an Advanced Propulsion Centre-funded project.

New and aged cylindrical type 21700 cells with NMC chemistry have been studied in thermal runaway investigations by means of accelerating rate calorimetry. Mechanical and thermal abuse on new cells was compared for different states of charge. Depending on the active material, the aging behavior and thermal runaway performance, as well as critical temperatures, are different and will be described.

This talk details a collaborative project between Sandia and Idaho National Laboratories to develop a diagnostic demonstration platform. As part of this, we describe the development and operation of a tool used to integrate battery failure diagnostics into battery modules and attempt to detect induced failures with various diagnostic tools. As a secondary goal we look to evaluate the ability of various diagnostic strategies to detect and arrest battery failure.

Future BMS will use physics-based models (PBMs) of Li-ion cells instead of the presently used equivalent-circuit models because PBMs can enable controlling batteries to effect a direct physically meaningful tradeoff between performance and service life. However, PBMs are mathematically complicated and difficult to formulate and use. This talk will introduce an open-source toolbox of MATLAB code (a companion to the soon-to-be-released book: "Battery Management Systems, Volume III: Physics-Based Methods") that facilitates developing and simulating PBMs of Lithium-ion battery cells.

Accurate and reliable electric vehicle battery management is crucial for safe and effective operation, especially considering today’s high-performance systems. Reduced-complexity battery models and advanced estimation and control algorithms have the potential to improve battery performance and extend life. This presentation introduces an open-source MATLAB-based toolbox companion to the soon-to-be released "Battery Management Systems Volume III: Physics Based Methods" which allows the user to experiment with new techniques.

Using model-based control strategies, we have developed optimal charging protocols to minimize the capacity fade due to SEI-layer formation, lithium-plating, and intercalation-induced stresses, while controlling internal temperatures inside the batteries. In collaboration with NREL, we have shown increase in cycle-life by more than 100%. We will present further results for faster charging and improved battery life on 2.2kWh battery modules.

Solid-state Lithium-ion batteries are predicted to become mainstream in the next few years due to their superior performance, such as high energy density (350Wh/kg), wide operating temperature (-10 to 70C), excellent safety, and lower cost. Solid-state batteries also offer a higher cell voltage of nearly 5V. However, the life cycle of the solid-state batteries may be much lower than the current Lithium-ion battery. Hence, a new generation of battery management systems is necessary to manage the future solid-state Lithium-ion batteries that can handle the high cell voltage and optimize the life cycle.

Considering the CO2-footprint of battery packs, as well as space, weight and costs of a battery pack, we are looking into reducing non-cell battery components to a minimum. How many BMS and E/E components are needed to make a best-in-class battery pack safe and reliable while keeping the system lean and its BOM items minimal? In our talk we'll look into actuators for switching and fusing, electronics for sensing and processing power needs as well as mechanical integration opportunities.

Fast charging can readily lead to early cell failure and reduced performance. The ability to use cell parameters for the development of advanced charge protocols provides an opportunity to tailor both the time and energy accepted to specific needs while minimizing degradation. During this talk, advanced protocols and analysis including the use of machine learning to identify failure modes and predict performance will be discussed. Key items include: Modified protocols based on advanced electrolytes and electrode design, Machine-learning methods to classify and quantify degradation modes, Future gaps in fast charging including scaling protocols.

This presentation details a dynamic charging system, achieving an unlimited EV cruising range by charging the EV at high power during cruising. This system would help make it possible to finish battery charging in a short time by contact with the EV while cruising and enable drivers to freely cruise their intended routes after charging.

Tests were performed inside our fractional thermal runaway calorimeter to quantify the heat transferred and its distributions and those runs done at a synchrotron yielded fascinating very high speed X-ray videography. These show tolerance to nail penetration and activation of defect internal shorts and when thermally forced into thermal runaway, the heat output is significantly reduced.

We developed a new innovative battery assembly technique to integrate composite structures with Li-ion batteries to substantially reduce the overall system weight while maintaining the energy capacity. Ultrasonic sensors are also embedded inside the structures to monitor the health of the batteries (SOH) as well as structures (SHM) during operation remotely or in demand.

Battery pack design requires substantial protective measures to keep physical separation between the electrodes of opposite polarity under external impact to avoid short circuit. We demonstrate that the addition of inert nanoparticles to a standard liquid electrolyte creates a shear thickening electrolyte which stiffens upon the application of external dynamic load. Such electrolyte prevents the electrodes from shorting and returns to the liquid state once the load is removed. Benefits of shear thickening electrolyte are discussed.  Methods for electrolyte integration into the separator are discussed. Ballistic testing and cell performance are demonstrated.

The transfer of theoretical approaches from research to development has a number of stumbling blocks for lithium-ion cells that can be avoided. Especially for a fast implementation of these new research approaches into real experimental samples to be industrially produced and applied, this talk addresses core elements and lessons learned for this. These points are based on high development speed, market access to materials, technology knowledge, experience and the courage to try out new technologies and bring them into mass production.