Lithium-Ion Battery Temperature Sensing for EVs

Intelligent vehicle system that predicts and responds to thermal runaway events in vehicle batteries when parked in enclosed spaces. The system detects battery cell overheating and determines if the vehicle is parked in an enclosed area using sensors and vehicle data. If so, it alerts nearby people and first responders about the thermal event and provides instructions to evacuate the area. This mitigates risks from battery fires when parked indoors. The system also disconnects the battery to prevent spreading.

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A monitoring and protection system for energy storage devices like batteries that provides real-time monitoring and protective actions to mitigate failures and enhance safety. The system has temperature and deformation sensors on each battery module. A control unit receives the data and triggers protective actions based on the readings. This allows proactive response to abnormal conditions like overheating or deformation, preventing cascading failures and catastrophic events like fires.

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Accurately estimating the temperature of a hotter area inside a battery module using a temperature sensor located in a cooler area. The technique involves adding a correction term to the sensor reading that scales with the rate of change of the sensor value. This prevents the estimated temperature from overshooting when the sensor is affected by noise. The correction term is set such that the estimated temperature rise rate in the hotter area doesn't exceed a predetermined value.

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Real-time temperature measurement for traction battery packs using deep learning to improve accuracy compared to traditional methods. The technique involves using a generative adversarial network (GAN) with a three-dimensional convolutional neural network to infer the battery pack's full temperature field from limited measured points. It leverages the GAN's generative capability to generate a 3D temperature field that matches the measured data. This preserves the spatial correlation of the pack temperature distribution.

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Battery module design to accurately measure internal temperature for improved performance at high discharge rates. The design involves compressing a thermistor against the top cover of the battery using a component on the external wiring harness board. This forces the thermistor to contact the cover and accurately detect its temperature. The cover temperature closely matches the internal battery temperature. By measuring the cover instead of the external sheet, it provides a more accurate representation of the battery's internal temperature as the cover closely follows the battery temperature changes.

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Battery design with through-stack fasteners and channels for improved monitoring, cooling, and swelling compensation. The battery has multiple circuit boards with aligned apertures through the active cell regions. Fasteners extend through these channels to connect the circuit boards. Conductive extensions on the cells connect to the fasteners. This allows monitoring, cooling, and swelling compensation through the fasteners instead of internal probes. The fasteners also provide electrical connections between cells and thermal paths for cooling. The channels allow heat transfer and swelling compensation across the cell stack.

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Temperature sampling assembly for batteries to improve reliability and accuracy of temperature monitoring. The assembly has a modular design with a sampling circuit board that can be detached from the battery component being measured. This prevents adhesive failure and sensor detachment due to high temperatures. The circuit board has a sampling part with a temperature sensor chip, connected to a heat spreading base via adhesive. The base conducts component heat to the chip. The base can then attach to the battery component. Flexible adhesive on the board allows expansion/contraction mismatch without breaking. This assembly allows independent modular temperature sensing that can be moved between components without adhesive loss.

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Abstract Large prismatic cells are increasingly being used as the primary power source in transportation applications. Effective online thermal management of these is crucial for ensuring safety and maximizing performance. However, significant discrepancies between surface internal temperatures make it difficult to detect anomalies promptly, which hinders effective increases risk irreversible hazards. This paper introduces an innovative technology Liion batteries. By exploiting temperature sensitivity ultrasound velocity applying tomographic reconstruction based on surrounding measurements, enables detailed crosssectional imaging. allows nondestructive, realtime visualization temperatures. Furthermore, with its compact design costeffectiveness, this suitable insitu deployment, offering a precise feedback mechanism management. Demonstrations conducted during continuous discharging scenarios have shown that system can identify hightemperature regions near tabs remain undetected by thermocouples. advancement has potential significantly reduce fires or explosions whi... Read More

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Efficient thermal management of lithium-ion batteries is crucial for electric vehicle safety and performance. This study investigates immersion cooling in serpentine channels 18650 batteries, aiming to identify key factors affecting maximum battery temperature (Tmax) pump power (Pw). A Box-Behnken experimental design implemented with Computational Fluid Dynamics simulations analyze responses Tmax Pw. Five variables are defined: partition length (Lp), charging/discharging rate (Crate), coolant volumetric flow (V), inlet (Tin) ambient (Tamb). Statistical significance evaluated via Analysis Variance. The results show that: Tin dominated Tmax, followed by Crate, V, Lp. Significant interactions (VTin VTamb) observed. For Pw, V V extreme significance, while Lp effects were minor. Interaction LpV was significant but secondary. After optimization minimize Tave the optimal values Lp, Tin, Tamb determined be 89.5 mm, 1.08 C, 0.51 LPM, 20 C, 25.62C respectively. corresponding optimized are: = 22.87C, 21.67C, Pw 0.279 mW. Optimal requires prioritizing control suppression regulati... Read More

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In this investigation, a comprehensive validation framework for an integrated electrochemical-thermal model that addresses critical thermal management challenges in lithium-ion batteries (LIBs) is presented. The two-dimensional numerical combines the NewmanTiedemannGuKim (NTGK) battery with enthalpy-porosity approach phase change material (PCM) systems (BTMSs). Rigorous against benchmarks demonstrates models exceptional predictive capability across wide range of operating conditions. Simulated temperature distribution and voltage capacity profiles at multiple discharge rates show excellent agreement experimental data, accurately capturing underlying mechanisms. Incorporating Capric acid (with transition 302305 K) as PCM, significantly improved accuracy over existing models literature. Notable error reductions include 78.3% decrease Mean Squared Error (0.477 vs. 2.202), 53.4% reduction Root (0.619 1.483), 55.5% drop Absolute Percentage Error. Statistical analysis further confirms robustness, high coefficient determination (R2 = 0.968858) well-distributed residuals. Liqu... Read More

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Battery cell design with integrated distributed temperature sensing using optical fibers. Multiple grating temperature measurement points are formed on an optical fiber that is arranged on the battery cell body. This allows precise and distributed temperature monitoring of the cell without requiring external thermistors. The grating structure on the optical fiber reflects specific wavelengths when temperature changes, providing distributed temperature sensing points along the fiber.

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This study presents an experimental investigation of a novel hybrid battery thermal management system (BTMS) that integrates solenoid-actuated Peltier-based heat sink with CuO/ethylene glycol (EG) nanofluid coolant loop. The delivers on-demand cooling through time-controlled thermoelectric operation, enhancing temperature regulation during surges. Experiments were conducted CuO nanoparticle concentrations ranging from 0.5% to 2.0% (vol.) and flow rates 1 5 LPM, at inlet 50C ambient 26C. Performance metrics such as drop, transfer rate, overall coefficient analyzed. Results showed maximum enhancement 40.63% (tube-side) 38.64% (air-side) CuO. Compared conventional liquid system, the setup demonstrated 7.01% higher rate improved variation control (up 28.53%). Life Cycle Cost (LCC) analysis demonstrates 25%30% reduction in long-term costs 36% life extension, supporting systems economic viability. scalable, energy-efficient BTMS offers promising solution for advanced electric vehicles requiring high-precision control.

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Monitoring battery systems like electric vehicle batteries to detect and prevent thermal runaway events during inactive periods when the battery management system is powered down. The method involves using sensors to continuously monitor cell voltages and temperatures when the system is not in use. If a predefined wake-up time passes, a new wake-up time and default values are calculated based on measured value gradients and limits. This allows waking the system earlier to prevent runaway if gradients indicate approaching limits. If measured values exceed limits, it's an emergency and the system wakes immediately. This improves safety by catching runaways sooner during inactive periods.

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A good thermal management system for batteries is the key to solving potential risks such as runaway of and ensuring that work within appropriate temperature range. To resolve conflict between cooling efficiency input power in existing battery systems based on thermoelectric cooling, this paper proposes an optimization method layout devices. Using a multi-physics coupling numerical model, study focuses analyzing impact quantity devices current temperature. The optimal arrangement structure response characteristics are investigated from four aspects: maximum temperature, difference, difference uniformity, coefficient. research results show optimized capable reducing both pack, reduces consumption by 19.8%, effectively enhancing energy system.

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The study presents a thorough theoretical analysis of the thermal distribution in electric vehicle battery packs under different heating loads. A finite-element heat transfer model is developed COMSOL to simulate pack with 15 cylindrical lithium-ion cells integrated liquid-cooled support plates. C-rates, which define generation during charge-discharge cycle, are included model-in real case scenarios wherein 10 Ah generates outputs about 10.5 W, 25 and 54 W at 3C, 5C, 8C charge rates, respectively. Transient simulations display how temperature profiles evolve time reach quasi-steady states by input counterbalanced dissipation through convection. It also examines air convection performance as technique for cooling, revealing that while it cheaper simpler implement, less effective than liquid cooling. Other alternatives this regard, such use graphite foam, have been investigated concerning their ability achieve higher coefficients, thus enhancing load management greater rates charge. results illuminate importance optimized systems avert runaway EV ensure safety, efficiency, longevity. w... Read More

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Battery prognostics tool that can predict and alert for thermal runaway events in batteries even when the battery management system (BMS) is turned off or failed. The tool uses cell temperature sensors to monitor cells when the BMS is not operational. It compares the cell temps to a thermal model to predict runaway risk. If a runaway is predicted, an alarm is output to alert of the potential issue. This allows early warning of runaway even when the BMS is not functional.

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Early fire risk detection in vehicles using optical fiber temperature sensors placed near critical components like batteries, fuel cells, pumps, etc. The sensors have a tunable light source, interferometer, detector, and signal processing module. The sensors use a short periodic light source waveform and wavelength tuning to achieve high spatial resolution temperature monitoring. The sensors detect temperatures exceeding thresholds and generate alarms. This allows early warning of overheating components before fires start.

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Vacuum pressure sensor with a contamination shield to prevent sensor degradation due to process contamination. The sensor has a diaphragm and electrode forming a capacitive structure in a sealed cavity. A support structure holds the diaphragm. A contamination shield between the inlet and diaphragm provides fluid paths crossing the diaphragm plane multiple times. This allows media to reach the diaphragm without direct exposure through the inlet, preventing contamination accumulation. The shield can have apertures, walls, and labyrinths to guide the paths.

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In the context of global energy transition, thermal management electric vehicle batteries faces severe challenges due to temperature rise and consumption under dynamic operating conditions. Traditional strategies rely on real-time feedback suffer from response lag efficiency imbalance. this study, we propose a neural network-based synergistic optimization method for driving conditions prediction management, which collects multi-scenario real-vehicle data (358 60-s condition segments) by naturalistic collection method, extracts four typical (congestion, highway, urban, suburbia) combining with K-means clustering, constructs BP (backpropagation network) model (20 neurons in input layer 60 output layer) predict speed next s. Based results, coupled PID control mechanism dynamically adjusts coolant flow rate (maximum reduction 17.6%), reduces maximum battery 3.8 C, difference 0.3 standard deviation fluctuation at ambient temperatures 25~40 C is 0.2 AMESim simulation experimental validation. The results show that strategy significantly improves safety system economy complex working pro... Read More

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Abstract Lithiumion batteries play a crucial role in reducing carbon emissions and promoting the use of electric vehicles. There are numerous input variables influencing thermal profile lithiumion batteries. Therefore, precise assessment relative contributions various factors is essential for optimizing management control processes. In this study, we tested battery pack composed five 14.6 Ah prismatic cells connected series under different discharge rates (2C, 3C, 4C, 5C), ambient temperatures (30, 35, 40, 45C), convective heat transfer coefficients (5, 10, 20, 40 ). Results showed that temperature with contribution 58.01% had strong influence on maximum temperature. Furthermore, influences Crate coefficient were identical. Moreover, it was found homogeneousness very sensitive to Crate, contributing 71.07% increase difference. To ensure uniformity at same time, moderate temperatures, low Crates, high can be preferred. Consequently, statistically obtained results study may contribute towards performance optimization improved safety packs.

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