(Keynote) on the Challenges and Opportunities for Parameterizing Multi-Physics Battery Models with Expansion Measurements
Authors: Siegel Jason 
Published: December 2024

Lithium-ion batteries are projected to reach cost targets making them competitive with internal combustion engines for light-duty transportation within the decade [1], which will help drive demand for EVs. Upcoming regulations in Europe, China, and the United States for automotive safety and durability will drive the design of battery systems, and the algorithms for battery management over the next decade. The Global Technical Regulation 20 (GTR20) describes the safety requirements for electric vehicle battery systems. In particular, the proposed regulation addresses the need for early detection and warning of occupants about battery faults and failures. The warning should allow for egress 5 minutes prior to the presence of a hazardous situation inside the passenger compartment caused by a battery cell thermal runaway. However, detecting the failure with enough time can be difficult using the current production battery sensor suites.

Durability assessment for Lithium-ion batteries is also tricky because these systems are designed to live for more than 10-15 years, so testing under representative conditions could exceed multiple product development cycles. Accelerated aging tests can shorten the testing time to reach the product's end-of-life conditions, typically defined as 70 or 80% state of health, but a deep physical understanding of the degradation modes that are accelerated by the testing is required to project these results back to the real-world use case and warranty period. Due to the many possible definitions of battery State of Health (SoH) which can be related to both capacity loss and internal resistance growth, the Global Technical Regulation 22 (GTR22) defines their durability requirements in terms of two new related metrics: the State of Certified Energy (SOCE) and the State of Certified Range (SOCR). Both metrics represent a percentage of the certified battery energy or electric range remaining at a given point in time. The SOCE is based on the Society of Automotive Engineers (SAE) metric of Usable Battery Energy (UBE). The GTR22 will also require a way for the consumer to read battery health information and usage data from the vehicle.

Physics-based battery models which include degradation mechanisms have great promise in addressing many of these challenges due to the relationship between modeled design parameters and the resulting device performance and durability. The models can enable virtual engineering to assess design tradeoffs before building the first prototype, however, parameterizing these models can be difficult due to the large number of parameters. In this presentation, we will explore the challenges of parameterizing physics-based battery models using conventional current, voltage, and temperature measurements. We will show how the measurement of the cell expansion in the laboratory setting and the fixtures that support the testing [2]. The augmentation of expansion data can inform model development and parameterization of a Single Particle Model with electrolyte dynamics (SPMe) implemented in the PyBaMM (Python Battery Mathematical Modelling) framework [3]. Next, we will demonstrate how the sensor data could be paired with the models to augment diagnostic algorithms to infer electrode-level aging phenomena, improve the state of charge estimation, and provide an early warning of gas generation before cell venting. Finally, we will discuss the practical implementation issues in packaging temperature and strain sensors in automotive battery modules and packs.

[1] C. Shen, P. Slowik, A. Beach. “INVESTIGATING THE U.S. BATTERY SUPPLY CHAIN AND ITS IMPACT ON ELECTRIC VEHICLE COSTS.” Feb 2024, ICCT REPORT

[2] S. Pannala, A. Weng, I. Fischer, J.B. Siegel, and A.G. Stefanopoulou, “Low-cost inductive sensor and fixture kit for measuring battery cell thickness under constant pressure.” 2022, IFAC-PapersOnLine, 55(37), 712-717.

[3] Sravan Pannala et al 2024 J. Electrochem. Soc. 171 010532