Battery state-of-power (SOP) is paramount for power split control in hybrid electric vehicles (HEVs) and overall vehicle performance and drive-ability for xEVs. It consists of estimating available charge/discharge power that the battery can source/sink over a specific time. Methods relying on a single model to describe the entire pack may be inefficient as they often neglect crucial cell-level information. This work demonstrates a bottom-up approach for SOP estimation where information from individual cells are used in the SOP calculation rather than pack-level only.

Battery state-of-power (SOP) is paramount for power split control in hybrid electric vehicles (HEVs) and overall vehicle performance and drive-ability for xEVs. It consists of estimating available charge/discharge power that the battery can source/sink over a specific time. Methods relying on a single model to describe the entire pack may be inefficient as they often neglect crucial cell-level information. This work demonstrates a bottom-up approach for SOP estimation where information from individual cells are used in the SOP calculation rather than pack-level only.

Battery management systems (BMS) are designed to achieve control objectives, one of which is pack performance management. This is done by estimating battery states, including state-of-charge (SOC), state-of-power (SOP), and state-of-health (SOH). Accurate and robust estimation of these states is desired over the entire useful life of the battery pack. This work presents a case study evaluating the reliability of a model-based battery state estimation framework, where we tested the algorithm on pack-level data from beginning, middle, and end of battery life.

Battery management systems rely on accurate state of charge estimation which rely on robust parameterisation of batteries, usually done during the preproduction stage. The parameterisation of batteries and subsequent validation can take a long time. Here we present our work on developing embedded sensors into automotive battery cells allowing measurement of electrode potentials and internal temperature. This gives an accurate real time measurement of battery state during various scenarios allowing quick parametrisation of batteries. The methodology is equally useful for designing charging routines as well as understanding the limits of safe operation.

In this study, the mechanical response of electrochemically aged Li-ion cells was analyzed for different loading conditions and compared with fresh cells. The goal of this study was to understand the effect of degradation mechanisms in quasi-static but also dynamic loading conditions. It was found, that the change in the cell structure due to aging (e.g.; formation of SEI, reduction of electrolyte, material cracking, …) significantly influences the mechanical response of the cells.

An NMC 811 21700 cell module is subjected to immersion cooling during fast charging and nail penetration testing. The results are compared to baseline without immersion cooling and benefits and shortcomings are analyzed.

As Electric Vehicles (EV) continue to play a larger role in the future of the automotive industry, circuit protection is becoming more and more vital. This presentation highlights some concerns associated with the conventional fuses and explains why AEM fuse technology offers performance and safety for system critical EV applications.

The Battery Safety Science Research team at Underwriters Laboratories has carried out research using different materials and designs to reduce or eliminate thermal runaway propagation in lithium-ion cells and modules. The presentation will cover research findings on methods and designs to mitigate thermal runaway in shipping containers that transport cells and batteries for automotive applications. Mitigation methods in modules with electrically interconnected cells will also be presented.

To protect passengers from the negative impact of thermal runaways, standards like GB 38031-2020 are introduced. One way to comply with these is to prevent hot particles, created by cell explosion, from being ejected to the environment, so they cannot ignite flammable gas/air mixtures outside the pack. Adding hot particle filter functionality to venting units as shown in the presentation is an innovative solution addressing these new requirements.

Presentation will focus on Battery Safety topics.

The race for the best cell format is open: From cylindric to pouch to prismatic approaches, all formats are currently out on the automotive battery market. In our talk we will shed light on the pros and cons of different formats and share insights we gained by opening and physically modelling a large variety of the cells, which are currently on the market.

In high volume cell production, the parameters differ from those of premium cell production. Premium cell production requires a high development speed, market access, technology knowledge, hands-on mentality and courage to try out new technologies and bring them into series production. New materials already require state-of-the-art production processes and environments in series development. But to achieve outstanding performance values in the battery cell, new concepts must be engineered to series maturity in materials and production processes.

Heat processing of new battery materials in industrial quantities can be challenging. ONEJOON´s unique approach provides a large contribution to grant a fast upscale at low risk. With it´s test center and extensive simulation expertise, ONEJOON helps to define the parameters needed for the definition of a production concept. It can choose from a wide range of proven kiln systems to establish the most capable kiln line.

Future BMS algorithms will use physics-based reduced-order models (ROMs) of Li-ion cells instead of the presently used equivalent-circuit models because these ROMs can enable controlling battery systems to effect a direct physically meaningful tradeoff between performance and service life. However, many ROMs give the best predictions only in small regions around specific operating conditions. This talk will show how to apply nonlinear Kalman filters efficiently to a family of ROMs so that the filter’s state estimates are valid over a wide battery-pack temperature and SOC operating window.

Accurate and reliable electric vehicle battery management is crucial for safe and effective operation, especially in light of today’s high-performance systems. Physics-based models enable advanced control actions based on dynamic electrochemical measures but are prohibitively complex for embedded architectures. This work compares several reduced model forms to assess their accuracy, computational complexity, and amenability for use in advanced control algorithms.

AVL’s series battery benchmarking program provides a database for objective comparison in technical attributes, as well as in engineering methodology, for BEV battery market competitors for clear-system, target definition of high-performing, reliable, and safe batteries. Two hundred-seventy different criteria are evaluated through AVL benchmarking metrics displayed in 8 high-level attributes. The found integrated system performance values are pointed out to support current and future development programs.

Understanding the risks associated with thermal runaway of Li-ion batteries is critical for designing safe cells and battery systems. The thermal response of cells can greatly vary for identical cell designs tested under identical conditions, the distribution of which is costly to fully characterize experimentally and cannot be captured by deterministic models. The Battery Failure Databank contains robust, high-quality data from hundreds of abuse tests spanning numerous commercial cell designs and abuse testing conditions. Data was gathered using a fractional thermal runaway calorimeter and contains the fractional breakdown of heat and mass from ejected and non-ejected cell contents, as well as high-speed radiography of the internal structural response of cells during thermal runaway. This presentation will provide an overview of the insights gained from the Battery Failure Databank on general trends in thermal runaway behaviors for different cell designs under different abuse conditions.

Here we demonstrate a distributed heat load approach as an alternative and less computationally expensive analysis technique for thermal runaway and cell-to-cell propagation. Previous testing was conducted to evaluate materials selection and state-of-charge impacts for transportation boxes containing Li-ion cells. A conduction and radiation driven thermal model using a distributed heat load approach for thermal runaway heating was developed and the results of which are presented here.

While almost every OEM is working on new platforms, there is little standardization in the design of battery packs. From different cell chemistries and form factors to different performance requirements, no two designs are the same. Thermal management solutions also vary widely, in particular the thermal interface materials used in battery packs.