On-board monitoring of 2-D spatially-resolved temperatures in cylindrical lithium-ion batteries: Part II. State estimation via impedance-based temperature sensing

Impedance-based temperature detection (ITD) is a promising approach for rapid estimation of internal cell temperature based on the correlation between temperature and electrochemical impedance. Previously, ITD was used as part of an Extended Kalman Filter (EKF) state-estimator in conjunction with a thermal model to enable estimation of the 1-D temperature distribution of a cylindrical lithium-ion battery. Here, we extend this method to enable estimation of the 2-D temperature field of a battery with temperature gradients in both the radial and axial directions. An EKF using a parameterised 2-D spectral-Galerkin model with ITD measurement input (the imaginary part of the impedance at 215 Hz) is shown to accurately predict the core temperature and multiple surface temperatures of a 32113 LiFePO$_4$ cell, using current excitation profiles based on an Artemis HEV drive cycle. The method is validated experimentally on a cell fitted with a heat sink and asymmetrically cooled via forced air convection. A novel approach to impedance-temperature calibration is also presented, which uses data from a single drive cycle, rather than measurements at multiple uniform cell temperatures as in previous studies. This greatly reduces the time required for calibration, since it overcomes the need for repeated cell thermal equalization.Comment: 11 pages, 8 figures, submitted to the Journal of Power Source

A Flexible Three-in-One Microsensor for Real-Time Monitoring of Internal Temperature, Voltage and Current of Lithium Batteries

Lithium batteries are widely used in notebook computers, mobile phones, 3C electronic products, and electric vehicles. However, under a high charge/discharge rate, the internal temperature of lithium battery may rise sharply, thus causing safety problems. On the other hand, when the lithium battery is overcharged, the voltage and current may be affected, resulting in battery instability. This study applies the micro-electro-mechanical systems (MEMS) technology on a flexible substrate, and develops a flexible three-in-one microsensor that can withstand the internal harsh environment of a lithium battery and instantly measure the internal temperature, voltage and current of the battery. Then, the internal information can be fed back to the outside in advance for the purpose of safety management without damaging the lithium battery structure. The proposed flexible three-in-one microsensor should prove helpful for the improvement of lithium battery design or material development in the future

In-situ instrumentation for smart energy storage

Lithium-ion technology is an increasing choice for battery powered systems, offering long-lasting, reliable and efficient energy storage. However, significant safety and performance challenges within the technology are still apparent. The current state of the art for monitoring cells performance is typically based on observing full cell voltage and occasional temperature sensor on the skin of a cell. Consequently, it is extremely difficult to track cells’ health within complex, especially high-performance, battery systems. Therefore, a new way of characterising cells’ is required. Here we show the design and manufacturing methods of transforming normal cells into smart systems. The sensor topologies embedded into the cells were electrical temperature, electro-chemical and optical temperature sensors. This enabled in-situ and operando thermal and electrochemical data collection during cells’ real-life operations. In this work, the impact of the sensors upon the cells performance has been shown to be negligible, with over 100 cycles conducted, versus unmodified cells for both pouch and cylindrical formats. This was validated using time and frequency domain analysis. A significant temperature difference was identified between the cell’s core and can temperatures of up to 6 °C during discharge and 3 °C during charge phase. Therefore, this work illustrates the necessity of internal cell temperature measurements for thermal management and safety validation. Lastly, with the aid of the in-situ measurement tools, certain cells can be further optimised without compromising thermal safety limits, while under particular scenarios safety limits can be breached earlier than the external sensors would indicate, showing how paramount in-situ data is to the operational safety

Marine NMEA 2000 Smart Sensors for Ship Batteries Supervision and Predictive Fault Diagnosis

[EN] In this paper, an application for the management, supervision and failure forecast of a ship¿s energy storage system is developed through a National Marine Electronics Association (NMEA) 2000 smart sensor network. Here, the NMEA 2000 network sensor devices for the measurement and supervision of the parameters inherent to energy storage and energy supply are reviewed. The importance of energy storage systems in ships, the causes and models of battery aging, types of failures, and predictive diagnosis techniques for valve-regulated lead-acid (VRLA) batteries used for assisted and safe navigation are discussed. In ships, battery banks are installed in chambers that normally do not have temperature regulation and therefore are significantly conditioned by the outside temperature. A specific method based on the analysis of the time-series data of random and seasonal factors is proposed for the comparative trend analyses of both the battery internal temperature and the battery installation chamber temperature. The objective is to apply predictive fault diagnosis to detect any undesirable increase in battery temperature using prior indicators of heat dissipation process failure¿to avoid the development of the most frequent and dangerous failure modes of VRLA batteries such as dry out and thermal runaway. It is concluded that these failure modes can be conveniently diagnosed by easily recognized patterns, obtained by performing comparative trend analyses to the variables measured onboard by NMEA sensors.García Moreno, E.; Quiles Cucarella, E.; Correcher Salvador, A.; Morant Anglada, FJ. (2019). Marine NMEA 2000 Smart Sensors for Ship Batteries Supervision and Predictive Fault Diagnosis. 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