Voltage and Current Monitoring Systems for EV Batteries

Diagnosing connection issues in battery packs and wiring to improve reliability and reduce failures in electric vehicles. The diagnosis involves measuring current, voltages, and resistance of the battery pack, bus bar, and wires. By analyzing these parameters, the connection status of the bus bar and wires can be determined. This allows detecting issues like loose connections, short circuits, or broken wires that may not be evident from just monitoring the bus bar alone.

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Stacked electrode assembly with in-stack sensors for lithium-class batteries like Li-ion cells in vehicles. The assembly has working electrodes (anodes and cathodes) separated by insulating separators. Sensing leads on the separators contact specific regions of electrodes to measure voltage. A reference electrode connected to the leads provides signals to external sensing devices. This allows distributed electrode voltage mapping inside the stack without contacting individual cells.

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A failure detection method and system for battery racks that can predict and prevent overvoltage issues in battery packs. The method involves monitoring voltage and temperature data from the battery racks over time. It checks for spikes in voltage variability, computes trends and slopes, and synthetically evaluates voltage trend changes to detect potential overvoltage precursors. This allows anticipating overvoltage conditions before they cause failure.

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Estimating the state of health (SOH) of a rechargeable battery using a method that involves measuring current and voltage during charging, applying the Generalized Fluctuation-Dissipation Theorem (GFDT) to obtain battery response functions, deriving SOH parameters from those functions, and tracking changes in the SOH parameters with charge capacity to estimate SOH. This allows estimating and predicting battery health without additional equipment beyond what is already used for charging.

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Battery module with internal monitoring to check insulation of individual cells during manufacturing and after installation in electric vehicles. The module has a sensing block with an interface module to connect and measure voltage between the cell electrode tabs and pouch cut ends. This allows monitoring the insulation resistance of each cell pouch for quality control during manufacturing and detection of pouch corrosion or damage in installed batteries.

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Recent advancements in photovoltaic (PV) and battery technologies, combined with improvements power electronic converters, have accelerated the adoption of rooftop PV systems electric vehicles (EVs) distribution networks, while these technologies offer economic environmental benefits support transition to sustainable energy systems, they also introduce operational challenges, including voltage fluctuations, increased system losses, regulation issues under high penetration levels. Traditional Voltage Var Control (VVC) strategies, which rely on substation on-load tap changers, regulators, shunt capacitors, are insufficient fully manage challenges. This study proposes a novel Voltage, Var, Watt (VVWC) framework that coordinates operation EV resources, conventional devices, demand responsive loads. A mixed-integer nonlinear multi-objective optimization model is developed, applying Chebyshev goal programming approach balance objectives include minimizing curtailment, reducing flattening profile, not met. Unserved has, particular, been modeled incorporating concepts distributional recognit... Read More

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Abstract - A Battery Monitoring System (BMS) is an electronic setup designed to track essential parameters of rechargeable batteries, such as voltage, current, and State-of-Charge (SoC). By preventing overcharging over-discharging, systems help extend the lifespan reliability batteries. However, commercially available BMoS solutions are often costly unsuitable for budget-friendly embedded systems. Given widespread use Arduino Uno its affordability, open-source platform, user-friendly programming environment, this study aims develop a using microcontroller. The proposed system includes voltage current sensors, board, liquid crystal display (LCD) real-time monitoring. To achieve this, set out three primary objectives. First, it was necessary mathematically establish relationship between sensors' input output values. These mathematical expressions were then validated by observing sensor outputs under varying load conditions connecting disconnecting monitoring corresponding readings. Following complete prototype assembled integrating sensors LCD with Uno. tested 11.1 V Lithium-ion ba... Read More

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Apparatus, bus bar system, and method for accurately measuring electrical parameters of a bus bar in vehicles. The apparatus has two measuring systems attached to the bus bar - one for temperature and one for voltage. The readings are sent to an interface that combines them to determine electrical parameters like current, resistance, and power factor without needing a separate shunt resistor or temperature sensor. This provides more robust and precise measurements compared to traditional methods.

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Voltage detection circuit for battery packs that provides improved overcharge and low voltage detection accuracy even in cases of cell balance disruption. The circuit divides the battery voltage into two divided voltages using a bleeder resistance network. An overcharge comparator and switch monitor the first divided voltage. A low voltage comparator monitors the second divided voltage. A first low voltage switch is closed when the battery is fully charged and open when discharged, while a second low voltage switch is open when fully charged and closed when discharged. This configuration allows accurate overcharge and low voltage detection regardless of cell balance.

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Synchronous monitoring circuits and methods for battery management in electric vehicles and energy storage systems that provide reliable voltage, current, and temperature monitoring with high accuracy and reliability in harsh operating environments. The circuits use synchronous sampling techniques to mitigate noise issues and improve accuracy compared to single-channel ADC sampling. The synchronous sampling involves coordinating the sampling of multiple channels using a common clock signal to avoid timing misalignment and noise coupling. This provides more accurate and reliable data for battery management applications.

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Enhanced Battery Management Systems (BMS) are essential for improving operational efficacy and safety within Electric Vehicles (EVs), especially in tropical climates where traditional systems encounter considerable performance constraints. This research introduces a novel two-tiered deep learning framework that utilizes two-stage Long Short-Term Memory (LSTM) precise prediction of battery voltage SoC. The first tier employs LSTM-1 forecasts individual cell voltages across full-scale 120-cell Lithium Iron Phosphate (LFP) pack using multivariate time-series data, including history, vehicle speed, current, temperature, load metrics, derived from dynamometer testing. Experiments simulate real-world urban driving, with speeds 6 km/h to 40 variations 0, 10, 20%. second uses LSTM-2 SoC estimation, designed handle temperature-dependent fluctuations high-temperature environments. cascade design allows the system capture complex temporal inter-cell dependencies, making it effective under variable-load Empirical validation demonstrates 15% improvement estimation accuracy over methods driving co... Read More

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Battery cell design with integrated voltage sensing to simplify stack monitoring while reducing contact between the cells and external sensors. The cells have internal energy storage elements surrounded by sealed pouches. A conductive element inside the pouch connects the cathode terminal to a sensor terminal on the same side. This allows voltage sensing of the cathode without external contacts on the cell. The conductive element can be a wire or metallic layer piercing the pouch.

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This project introduces a smart electric vehicle (EV) system designed to make transportation cleaner, safer, and more efficient. It combines two ways of charging the using solar power traditional grid so that it can always stay powered, even if one source is unavailable. At heart an advanced Battery Management System (BMS) keeps battery healthy by monitoring its charge levels, balancing across cells, preventing damage. To ensure safety, also has thermal track temperature in real-time. If senses any risk overheating, take preventive action. All this data health, status, sent cloud IoT (Internet Things) technology, be monitored remotely from anywhere. setup helps maintaining vehicle, predicting issues before they happen, ensuring runs efficiently. By combining clean energy, monitoring, automation, aims support eco-friendly while improving safety Performance

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Battery management system that allows individual monitoring and control of battery cells without a complex web of wires. The system uses existing power cables between cells to transmit battery parameters and commands. A monitoring board on each cell monitors status and sends parameters to a central controller. The controller adjusts cell performance based on received data. This eliminates the need for extra wiring between cells and allows individual cell monitoring without grouping them into modules. The data is transmitted by injecting modulated signals onto the existing power cables.

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A method to accurately estimate the open circuit voltage of a chargeable battery regardless of dark current. The method involves measuring battery voltage and current, storing voltage values after charge/discharge, fitting a function to the stored voltages, calculating open circuit voltage using the fitted function, and discarding stored voltages if current or voltage fluctuates above a threshold. This prevents unreliable voltages due to current fluctuations from impacting the open circuit voltage estimation.

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This research investigates the modeling and analysis of a three-phase boost rectifier for DC fast charging systems electric vehicles (EVs). A mathematical model validated with MATLAB/Simulink simulations examines system behavior under various conditions. Performance in abc dq coordinate reveals high consistency theoretical calculations. The average voltage frame was found to be vd 685 V vq 0 V, discrepancy less than 0.1% from calculated values. However, current showed discrepancies due cross-coupling effects circuit impedance. Simulations reported id 211.50 iq 93.50 A, compared values 151.97 V. For output current, were 983.05 98.31 respectively. Three test cases analyzed, consist unbalanced conditions, drops, load step responses. Case 1 highest total harmonic distortion (THD), 2 increased THD further, 3 achieved lowest THD, demonstrating improved stability dynamic loads. These findings confirm systems minimal deviations predictions, enhanced quality, mitigation, efficiency EV applications.

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Abstract Lithium-based batteries (LiBs) are integral components in operating electric vehicles to renewable energy systems and portable electronic devices, thanks their unparalleled density, minimal self-discharge rates, favorable cycle life. However, the inherent safety risks performance degradation of LiB over time impose continuous monitoring facilitated by sophisticated battery management (BMS). This review comprehensively analyzes current state sensor technologies for smart LiBs, focusing on advancements, opportunities, potential challenges. Sensors classified into two primary groups based application: optimization. Safety sensors, including temperature, pressure, strain, gas, acoustic, magnetic focus detecting conditions that could lead hazardous situations. Performance optimization such as optical-based electrochemical-based, monitor factors charge health, emphasizing operational efficiency lifespan. The also highlights importance integrating these sensors with advanced algorithms control approaches optimize charging discharge cycles. Potential advancements driven nanotechnolo... Read More

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LiFePO4 batteries need a battery management system (BMS) to improve performance, extend their lifespan, and maintain safety by utilizing advanced monitoring, control, optimization techniques. This paper presents the design, development, implementation of an intelligent (i-BMS) that integrates real-time monitoring control batteries. The was extensively tested using multiple datasets, results show able temperature within set range, balance cell voltages, distribute energy according load prioritization. It uses fuzzy logic approach effectively manage farm requirements. Additionally, proposed method embedded three-level prioritization algorithm woven into rule allocate dynamically among essential, regular, non-essential loads.

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This project presents the development of an IoT-based Battery Management System (BMS) utilizing Random Forest Regressor machine learning model for remote battery health monitoring and optimization. The system integrates IoT-enabled sensors to collect real-time parameters such as voltage, current, temperature. data is transmitted through secure IoT gateways a cloud platform processing. employed predict critical metrics, including capacity degradation remaining useful life. enhances predictive accuracy enables informed decision-making optimized usage, thereby improving efficiency longevity. innovative solution demonstrates potential combining revolutionize management foster sustainable energy solutions.

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Multisine electrochemical impedance spectroscopy (EIS) represents a highly promising technique for the online characterization of battery functional states, offering potential to monitor, in real-time, key degradation phenomena such as aging, internal resistance variation, and state health (SoH) evolution. However, its widespread adoption embedded systems is currently limited by need balance measurement accuracy with strict energy constraints requirement short acquisition times. This work proposes novel broadband EIS approach based on multiband multisine excitation strategy which signal spectrum divided into multiple sub-bands that are sequentially explored. enables available be concentrated portion at time, thereby significantly improving signal-to-noise ratio (SNR) without substantially increasing total time. The result more energy-efficient method maintains high diagnostic precision. We further investigated optimal design these sequences, taking account realistic imposed sensing hardware limitations amplitude noise level. effectiveness proposed was demonstrated within comprehensiv... Read More

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Battery management system for electric vehicles with a refined voltage measurement technique to optimize battery performance and durability. The system manages an electric battery device with multiple modules connected in series, each containing cells. Some cells are connected by a busbar. The measurement technique accounts for busbar voltage offsets. It uses a single slave element to gather data from two modules. Measurements from cells on the busbar are adjusted based on the busbar resistance. This prevents overestimation due to busbar voltage. The adjusted cell voltages are used for safety methods like derating charging power. The technique improves accuracy by avoiding erroneous voltage readings from busbar cells.

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Method for accurately estimating the initial state of charge of a battery in a hybrid or electric vehicle, particularly when the battery has not been at rest for a long time. The method involves estimating an initial value of the state of charge during an initialization phase. The initialization phase includes steps like measuring the battery's voltage and current at the start of charging or discharging, calculating the current polarization based on the voltage and current values, and using the polarization to adjust the initial state of charge estimate. This takes into account the battery's polarization state to provide a more accurate initial state of charge estimate when the battery has not been resting for a long time.

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Protective circuit for high voltage, high current secondary battery applications like electric vehicle batteries. The circuit has a protective element with fuses, a heat generator, and terminals connected to the battery and auxiliary power. When an abnormality is detected, a control device switches an auxiliary power supply to energize the heat generator fuses, cutting off the battery from the external terminals. The heat generator fuses prevent excessive currents and voltages from damaging the battery. The auxiliary power allows high voltage fuses without voltage rating issues. The control device can detect abnormalities like overvoltage or overcurrent.

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Method and controller for accurately detecting voltages of battery cells in a battery pack using converters and switching units. The method involves routing the operating current from the battery cell anode through the converter to ground, while also routing a sampling current from the battery cell anode to the converter. This reduces the difference between currents through the anode and cathode paths, allowing the converters to accurately detect the cell voltage.

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The state of charge (STOC) lithium-ion batteries (LTIB) poses a significant challenge in the implementation and advancement battery management systems, necessitating precise measurement capacity utilized electric vehicle (EV) development, thereby emerging as straightforward issue. Efficient regulation energy, to mitigate dangers associated with overcharging over-discharging, is feasible only an accurate calculation STOCH, which supports several situations constraints. In STOCH esteem analysis, it imperative account for influence diverse components on operational cycle batteries, such cell aging imbalance, by employing various sophisticated similar circuit models batteries. Fitting assessment computations are employed quantify improve precision evaluations. systems (BMTS) essential vehicles (EVs). admiration, denoting excess limit or also constitutes central border BMTS. This approach use perpetual control value via Arduino UNO microcontroller. Additionally, we will examine display using simulation associate degree regulator utilizing MATLAB Simulink model. MATLAB, ANN model be develo... Read More

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Abstract - Electric vehicle battery packs need a complex Battery Management System (BMS) for vital parameter monitoring such as voltage, current and state of charge temperature to ensure safety together with operational efficiency. This research explores the BMS mechanisms which include external aging notifications through smoke detection followed by alarm sounds an optimal cooling system along automatic charging prevent degradation. Short-circuit protection devices in batteries decrease electrical failure risks can both fires dead batteries. The provides continuous power delivery real-time fast maintenance procedures under any possible condition. Key Words System(BMS), Vehicle Battery, Fire Protection, Thermal Management, Smoke Sensor, Short Circuit Real-time Monitoring, Safety, SOC.

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The increasing adoption of Electric Vehicles (EVs) has highlighted the need for efficient and safe charging systems. One major challenges in EV infrastructure is preventing overcharging, which leads to battery degradation, reduced lifespan, potential safety hazards. Therefore, this paper presents a Quick Response (QR)-based bulk system integrated with overcharge protection prevention mechanisms. A solar panel, an ATmega 328 microcontroller, Node MCU, battery, Liquid Crystal Display (LCD), IoT device are some components work. proposed utilizes QR code technology easy identification access control stations, enabling seamless user interaction. data gathered by sent users using IoT, it monitored BLYNK app. uploaded app cloud database via MCU module embedded inside microcontroller. It also integrates advanced based algorithms real-time monitoring protect against ensuring that EV's charged efficiently, safely, within its optimal capacity. This prevents incorporates smart algorithm monitors battery's state real-time.

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Diagnosing abnormalities in voltage behavior of batteries based on changes in differences between measured open circuit voltage data and estimated open circuit voltage data over time. The method involves generating open circuit voltage (OCV) data from the battery, deriving estimated OCV data based on the measured data, and diagnosing battery health based on the difference between the measured and estimated OCV values. This allows detecting subtle voltage abnormalities even when the battery voltage itself doesn't change significantly.

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Controlling battery charging to prevent lithium plating on anode surfaces through a novel voltage-based charging strategy. The approach measures the potential difference between reference and anode terminals in each cell and determines the charging current based on the minimum anode potential. This approach prevents lithium deposition by directly controlling the charging current based on the anode potential, eliminating the need for traditional lithium deposition rate measurement. The strategy ensures optimal charging conditions for each cell while preventing excessive lithium deposition.

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A diagnostic system for discharge circuits in electric vehicles that can detect if the discharge circuit is functioning properly. The system includes a sensor connected in series with the discharge circuit. During a diagnostic check, the control system operates the discharge circuit to dissipate charge. If the sensor detects no change in electrical characteristic, it indicates the discharge circuit is deficient and provides a notification. This allows proactive detection of faulty discharge circuits to prevent issues like incomplete charge dissipation during vehicle shutdown.

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Discharge device for secondary batteries that optimizes charging and discharging while maintaining battery health. The device employs a controlled discharge strategy that transitions from primary discharge to secondary discharge at specific voltage and current rates. This approach maintains the battery's state of charge while preventing excessive stress on the cells. The device includes sensors to monitor battery voltage, current, and temperature, enabling real-time adjustments to the discharge parameters. The controlled discharge strategy ensures safe and efficient battery management, particularly for batteries nearing the end of their lifespan.

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Predicting damage to battery cells by monitoring voltage and temperature within a damage range and calculating a weighting factor based on the readings. If the cell's voltage or temperature falls within the damage range, the cell is disconnected to prevent further damage. The weighting factor is accumulated over time to determine the overall damage level. If the accumulated weighting exceeds a threshold, the cell is permanently blocked. This allows managing cells based on damage history and replacing them at appropriate intervals.

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Battery monitoring system for electric vehicles that allows synchronized acquisition of battery voltage and current data without wired connections. The system uses wireless communication between a central monitoring device and individual battery measurement devices. The monitoring device sends voltage measurement commands to the battery devices at regular intervals. The battery devices measure voltage at those times. The monitoring device then synchronously acquires current data from onboard sensors during the same time intervals to match the voltage measurements. This allows calculating battery resistance without requiring precise timing coordination.

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Battery pack design and protection method to prevent reverse voltage damage when a cell fuse blows in a battery pack. The pack has balancing resistors, switches, and a current sensor between the pack terminals. If a cell fuse blows, the controller detects the increased pack current and turns on all the balancing switches to form a closed circuit through the resistors. This limits reverse voltage across the blown fuse to protect the cell. If a short is detected, it turns on all balancing switches. After a short, it checks for fuse blowout.

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Battery management system (BMS) using optical communication between batteries instead of wires to address issues like cyber-attacks, EMI, bulky wiring, and slow data transfer. The BMS has optical devices connected to each battery that emit and receive optical signals containing battery data through transparent and reflective films. The signals bounce between films to transfer between batteries. This allows fast, immune, and secure battery monitoring without wires.

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An electronic current control system for autonomous vehicles that automatically limits electrical current to pulsed or switching electronics like motors and LIDAR sensors without latency or user intervention. The system adds a current monitor component to the electrical pathway between the power supply, current control component, and pulsed/switching electronics. The monitor adjusts the current control component based on a threshold voltage compared to the output voltage, without needing the main processor. This provides faster, localized current limiting to prevent unsafe thermal events in the pulsed electronics.

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Battery diagnosis system that rapidly identifies low voltage cells in lithium-ion batteries through a novel approach combining voltage deviation analysis and rate of change detection. The system collects resting voltages during charging and discharging phases, calculates deviations from a representative baseline, and analyzes their rates of change over time. By comparing these deviations against predetermined thresholds, the system identifies cells exhibiting significant deviations from normal behavior, which are then further evaluated through linear regression analysis to confirm their low voltage status. This approach enables rapid and accurate identification of potential battery faults compared to traditional methods that rely solely on voltage readings.

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In this paper, a Battery Management System (BMS) is developed using the ESP32 micro-controller integrated with voltage and current sensors to enhance efficiency lifespan of batteries in electric vehicles (EV). The primary objective continuously monitor key parameters such as voltage, current, State Charge (SoC) Health (SoH) ensure optimal performance safety. Pulse Width Modulation (PWM) techniques are employed precisely regulate charging discharging processes, reducing energy losses preventing battery degradation. known for its low power consumption built-in Wi-Fi Bluetooth capabilities, acts central processing unit, collecting real-time data transmitting it cloud-based platform or local server further analysis. Advanced algorithms cell balancing provide accurate SoC SoH estimation, ensuring uniform charge distribution across cells. Additionally, BMS includes protection mechanisms against over-voltage, under-voltage over-current conditions, enhancing safety reliability.The proposed system offers cost-effective reliable solution management EV, focusing on efficient utilization, extend... Read More

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Compensating battery cell sampling voltages in a multi-module battery pack to accurately measure cell voltages. The method involves charging/discharging the pack with a stable current to determine impedance of cross-module busbars. This impedance is used to compensate voltages of cells near busbars. By checking all pack cells are normal first, it ensures accurate impedance calculations. This prevents voltage errors from long busbar lengths.

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A power storage pack for electric vehicles and charging stations that can efficiently measure contact resistance between the vehicle and charger after mounting to ensure proper connection and prevent issues like erroneous battery control. The pack has a controller that authenticates with the vehicle/charger using a current pattern over the power lines. By measuring voltages and current during authentication, the pack can determine contact resistance. This allows detecting any abnormal resistance changes due to loose connections, enabling proactive fault diagnosis.

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Differentiating and responding to short circuiting in batteries, particularly lithium secondary batteries, to improve safety and performance. The system involves detecting battery behavior during short circuits, comparing it to predetermined profiles, and taking appropriate mitigating actions based on the type of short circuit detected. This allows differentiating between different short circuiting behaviors and responding aggressively versus passively based on the analysis. The detection involves monitoring battery parameters like temperature, heat generation, current, voltage drop.

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System for mitigating degradation of batteries in electric vehicles by monitoring and managing operating conditions of individual battery modules. The system involves sensors on the modules to generate operational data, which is transmitted to a central component that analyzes the data to determine the module's operating condition. This allows identifying if the module is being operated in a way that accelerates degradation. By monitoring and managing module operating conditions, battery degradation can be mitigated.

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High-precision current detection method for lithium batteries and other applications that involves using a specialized integrated chip to accurately measure small currents without degradation from resistive losses or temperature drift. The chip has a current sampling switch connected in series with the protected current path, and a high-precision operational amplifier to amplify and convert the sampled current into a voltage signal. This amplified voltage is then read by a separate metering unit to provide an accurate representation of the original current. The amplification gain is adjusted based on the specific current loop parameters to optimize performance for different load current ranges. This allows precise current measurement using a small sampling resistor without sacrificing accuracy due to signal attenuation. The chip integrates the current sampling and metering functions to reduce interconnection issues and improve signal-to-noise ratio compared to separate components.

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Calculating state of charge (SOC) of a battery module during discharging to prevent sudden drop below a minimum allowed level. The method involves calculating a correction factor for SOC based on voltage, discharge current, and load resistance when the voltage is below a threshold. This speeds up SOC decrease so it reaches a preset value when the voltage drops to the minimum allowed level. This avoids abrupt SOC drops during discharging that could lead to abnormal consumption and user issues.

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Electrical module and battery pack design for improving voltage and temperature collection accuracy in electric vehicles. The design brings the cell voltage and temperature sensors closer to the module's electrical interface to reduce signal transmission length. This is done by integrating the sensor circuitry into the module instead of using separate sensors and cables. The module has a cells contact system to collect voltages and temperatures, and an on-board cell supervision circuit with analog front ends to convert the signals. This reduces the length of analog signal transmission compared to conventional designs with separate sensors and cables. The closer proximity of the sensors to the module interface reduces transmission path interference and improves voltage and temperature accuracy.

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Detecting abnormal cells in a battery pack with multiple cells connected in series or parallel blocks. The method involves monitoring relative voltage changes between cells during constant voltage (CV) charging. If a cell's voltage drops more than the others in CV, it indicates an issue like internal resistance increase. This allows detecting faulty cells without needing individual cell voltage thresholds.

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Method and system for estimating battery state of charge (SOC) that provides accurate and adaptive SOC estimation in various load, temperature, capacity, and aging conditions. The method involves calculating a voltage difference using a voltaic gauge and an open-circuit voltage. It then adaptively adjusts a gain using a gain control engine based on battery current and full charged capacity. This adjusted gain is used to generate the SOC change.

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Detecting defective battery cells in a battery pack to improve performance and longevity. The method involves monitoring the charge and discharge voltages of each cell over multiple charge/discharge cycles. If a cell consistently reaches full charge or empty discharge before others, it's flagged as defective after a certain number of cycles. This indicates accelerated degradation and potential issues like cell balancing and capacity loss.

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A battery management system that enables efficient and reliable monitoring of individual battery cells while maintaining the benefits of single-cell monitoring. The system comprises a battery management chip connected directly to a single battery cell, with the chip providing real-time cell-level monitoring and processing capabilities. The chip includes a data acquisition module, processing module, and communication module, with the processing module generating cell-specific data and the communication module transmitting this data to the control module. This architecture eliminates the need for complex wiring harnesses and connectors while maintaining the benefits of single-cell monitoring.

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Battery management system for detecting lithium plating on negative electrodes and identifying battery degradation due to internal short circuits. The system analyzes voltage and capacity curves to determine a target peak voltage, then compares it against this peak to identify side reactions. It also analyzes voltage and resistance profiles to determine resistance patterns indicative of internal short circuits. By combining these analyses, the system can accurately diagnose lithium plating and battery degradation through real-time monitoring.

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