This work presents an approach to monitoring the State-Of-Charge of Lithium-Ion battery cells via piezo disc-based ultrasonic Time-Of-Flight measurement by measuring the traveling time of a mechanical pulse through the cell between two surface-mounted sensors. The main advantage of this approach is the simplicity and the resulting low cost, which makes it suitable for future application in battery management systems. In detail, the excitation of the piezo actuator is done using a single semiconductor switch instead of a power amplifier, and the received signal is processed with an amplifier and Schmitttrigger combination to condition the signal for the microprocessor, which is part of a battery management system. Both the functionality and the limits of the design are evaluated with a high energy density Lithium-Ion pouch cell under different operational scenarios. Several parameters such as temperature, current rates, and excitation frequency are varied to prove the design concept. For validation purposes, an estimation function is generated and a real-world driving cycle applied. An estimation with an error of 1.29% of the Time-Of-Flight total value or 16.8%of the State-Of-Charge value under challenging conditions is achieved with the current setup.

Temperature is a crucial factor for the safe operation of lithium-ion batteries. During operation, the internal temperature rises above the external temperature due to poor inner thermal conductivity. Various sensors have been proposed to detect the internal temperature, including fiber Bragg grating sensors. However, to the authors’ knowledge, there is no detailed description of the encapsulation of the fiber Bragg grating sensor in the literature to shield it from strain. In this study, different encapsulation methods for strain compensation were compared to find the encapsulation material most compatible with the electrolyte. For this, we stored the proposed sensors with different encapsulation methods in ethylene carbonate:ethyl methyl carbonate (EC:EMC) 3:7 with LiPF₆ (lithium hexafluorophosphate) electrolyte and applied temperature changes. After evaluating the sensor encapsulation methods in terms of handling, diameter, uncertainty, usability, and hysteresis behavior, the most suitable sensor encapsulation was found to be a fused silica capillary with polyimide coating.

A typical method for measuring the radial thermal conductivity of cylindrical objects is the pipe method. This method introduces a heating wire in combination with standard thermocouples and optical Fiber Bragg grating temperature sensors into the core of a cell. This experimental method can lead to high uncertainties due to the slightly varying setup for each measurement and the non-homogenous structure of the cell. Due to the lack of equipment on the market, researchers have to resort to such experimental methods. To verify the measurement uncertainties and to show the possible range of results, an additional method is introduced. In this second method the cell is disassembled, and the thermal conductivity of each cell component is calculated based on measurements with the laser flash method and differential scanning calorimetry. Those results are used to numerically calculate thermal conductivity and to parameterize a finite element model. With this model, the uncertainties and problems inherent in the pipe method for cylindrical cells were shown. The surprising result was that uncertainties of up to 25% arise, just from incorrect assumption about the sensor position. Furthermore, the change in radial thermal conductivity at different states of charge (SOC) was measured with fully functional cells using the pipe method.

This work presents a method to determine the type of Lamb mode (antisymmetric or symmetric) that propagates through a lithium-ion pouch cell. To determine the type of mode and the group velocity at a specific frequency, two- and three-transducer setups were created. For these setups, it is important that all transducers have the same polarization direction. Two transducers are affixed to the center of the cell at a distance of several centimeters from each other so that the group velocity can be determined. Using cross-correlation, the group velocity of the emerging mode can be calculated. The measurement setup and the processing method was first validated with experiments on acrylic glass and aluminum plates. The measurements were supported with FEM simulations and a numerically calculated model. The output voltages of the receiving piezo-elements obtained in the FEM simulation are in agreement with the underlying theories. The phase shift, which results from the output voltage of the piezo-elements mounted one above the other on different sides of the plate, shows the type of mode. The results of the experimental determination of the Lamb mode that propagates through a lithium-ion pouch cell were validated with a numerically calculated multi-layer model and therefore validate this novel experimental approach.

Structural health monitoring (SHM) using piezoelectric transducers has been widely explored for individual lithium-ion cells, yet its applicability at the module level remains largely unstudied. This work demonstrates the feasibility of SHM on a realistic battery module composed of four 60 Ah pouch cells and operated in a mechanically constrained setup similar to an electric-vehicle (EV) battery environment. In this configuration, breathing-induced stack pressure varies during cycling, and these pressure changes are captured simultaneously with the parameters of the propagating guided wave using a self-developed ultrasonic battery management system (UBMS). Measurements at two C-rates and two ambient temperatures show that the group velocity shifts by approximately 32ms−1 between 25°C and 10°C, while cycling-induced stack pressure variations, corresponding to measured forces of up to 250 N, are reflected in a decrease of the normalized amplitude to values as low as 0.5. These findings demonstrate that piezoelectric SHM operates reliably in a realistic module-level environment. Moreover, it shows sensitivity to pressure changes within the cell stack, providing a foundation for future diagnostic approaches that are able to identify safety-critical states through their impact on the cell’s mechanical behavior.