EV Battery Lifespan Optimization

System for determining when to replace battery modules in vehicles based on calculated life estimations, enterprise acceptability values, and maintenance schedules. The system involves monitoring battery health parameters using onboard sensors, collecting vehicle and environmental data, analyzing the data to calculate battery life and health, comparing against enterprise acceptability thresholds, and communicating replacement determinations to the vehicle. This allows proactive replacement planning and optimization rather than waiting for failures.

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Battery monitoring system for electric vehicles that predicts battery life based on driving patterns to help optimize battery management. The system classifies vehicles into groups based on driving characteristics like speed variability. It estimates battery replacement cycles for each group and compares the vehicle's cycle to find a similar group. This allows drivers to see how their vehicle's battery compares to others in similar driving conditions, helping them optimize battery usage and replacement.

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A device that estimates future battery deterioration in vehicles. It uses historical data on battery usage and capacity retention to determine correlations between usage parameters and capacity loss. By extrapolating these correlations, it can predict when the battery's capacity will reach a specified threshold in the future. This allows proactive battery replacement planning based on estimated future capacity rather than waiting for actual capacity to drop.

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Displaying remaining life information for a battery system with replaceable modules to help optimize replacement decisions. The system calculates the current remaining life of the battery system based on the state of health (SOH) of all modules. It also calculates an extended remaining life if some modules are replaced with new ones. This extended life is shown alongside the current life to give users a comparison of how much extra life they could get by replacing modules versus keeping them. The user interface allows toggling between the two life estimates.

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A management system for electric vehicle (EV) batteries that notifies users when their battery needs replacement. The system estimates battery degradation based on usage history and sends alerts when a threshold is reached. This helps users replace batteries at the optimal time. The system also enables dealers to offer discounts for EVs with battery leases, incentivizing users to return batteries for reuse. The system uses a central management device to store battery data, estimate degradation, and transmit replacement alerts. The dealers can transmit alerts urging battery replacement to users. This ensures users replace batteries before they fail. The system also updates sales contracts to reflect battery leases.

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Method for determining the cost of replacing a battery in an electric vehicle in a more accurate and rational way. The method involves calculating two replacement costs: one based on current consumption and one based on battery degradation rate. It obtains the battery status when replacement is requested, including current consumption, target usage days, and performance parameters. Based on these, it determines the degradation rate and second replacement cost. This allows more precise battery replacement cost calculation compared to just using mileage or power consumption.

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Predicting battery degradation of electric vehicles like electric aircraft without actual vehicle testing to enable informed decision making about battery health and replacement. The method involves using a digital twin of the battery pack to simulate its operation and degradation. Battery data is collected from the pack monitor and fed into the digital twin. Periodically, the twin is updated with new pack data to refine the simulation. This allows predicting battery degradation levels and remaining capacity without limit testing the actual vehicle.

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Battery replacement method for power swap stations that improves safety of swapped batteries by considering vehicle performance and owner habits. When a vehicle requests battery replacement, the swap station analyzes vehicle data and driving behavior from the past period to determine the vehicle's electrical portrait and owner's electrical consumption portrait. It then matches a battery replacement strategy based on the battery risk level in that time period. Higher risk levels correspond to increased costs. This enables targeted matching of replacement strategies to mitigate risks based on vehicle and owner history.

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Intelligent battery maintenance method for extending the life of universal batteries like those used in electric vehicles. The method involves identifying, collecting, and analyzing operating data, marks, and alarms to determine when a battery needs maintenance. Degradation detection is performed on marked batteries using pre-detections under different conditions to calculate an accurate degree of deterioration. Based on the degradation results, personalized maintenance plans are generated for each battery. This allows targeted and optimized maintenance interventions to extend battery life compared to generic maintenance schedules.

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An intelligent battery management system for electric vehicles that uses data analysis to optimize battery performance, predict failure, and provide proactive maintenance. The system collects battery data from sold vehicles, analyzes health, predicts life, and alerts drivers of abnormalities. It also adjusts charging/discharging parameters based on battery condition. By monitoring and analyzing battery status in real-time, the system accurately predicts battery life, identifies issues, and proactively notifies drivers of maintenance needs.

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Battery management system for optimizing battery replacement in devices like electric vehicles. The system calculates the maximum current rate a replacement battery can handle based on its capacity and deterioration level. It then selects a replacement battery with an estimated maximum current rate matching a predetermined threshold. This ensures the new battery can handle the device's expected usage without excessive deterioration. The current rate calculation uses the original battery's usage history and expected usage period.

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Battery design that improves thermal management, ease of assembly and reduces cost while improving energy density in cylindrical cells. The battery uses a riveted pole that penetrates the cover plate to connect to the cell. The riveted pole allows cell connection without separate terminals, enabling flexible cell polarity arrangement during assembly. It also improves heat dissipation compared to traditional tabs. The riveted pole reduces complexity, parts count and cost while increasing energy density.

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Battery storage device for vehicles that allows inserting and removing EV batteries in a way that avoids damaging the terminals. The battery case has a mechanism to displace the case side terminal away from the battery terminal when inserting/removing. The mechanism is operated using a lever that first retracts the case terminal, then locks the battery in place. This prevents contact between the terminals until after insertion, avoiding damage if the battery is inserted roughly.

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Battery holder and battery holder arrangement for light electric vehicles that allows easy one-handed insertion, secure holding, and quick release of a vehicle battery. The holder has a pivoting latch mechanism with a rotating arm and extending tongue that automatically engages with the battery to lock it in place when inserted. A pivot surface on the fixed end of the holder provides a rotation point for the battery. The latch has spring and torsion mechanisms to extend and rotate the arm, and a locking unit to secure the latch closed.

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Battery pack design with an internal channel for securing sensing wires between battery cells. The battery pack has a frame with pillars and bent extensions that create spaces for the sensing wires. The wires can be easily inserted and held in place by the frame without needing adhesive. This simplifies wire installation compared to using tape or adhesive to secure them.

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Vehicle-based battery health monitoring system that collects real-time battery data from vehicles and analyzes it to diagnose battery failures and manage battery reuse. The system involves collecting battery data from vehicles, processing it, storing it, analyzing it using AI models to diagnose failures and predict issues, and providing monitoring and warnings to vehicle owners. This allows continuous battery health analysis using actual driving data to detect issues and optimize battery reuse.

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Method to optimize battery changing intervals for unmanned electric mining trucks to improve efficiency. The method involves evaluating the optimal time to replace batteries based on historical energy consumption data, current truck state, and driving conditions. It calculates the average energy consumption per cycle using historical data, and compares it to the current cycle energy consumption. If the current consumption is less than the average, it indicates there's still enough charge to complete the cycle. If the consumption is higher, it indicates a replacement may be needed. This adaptive evaluation considers factors beyond battery percentage to more accurately determine when to swap batteries.

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A method for optimizing battery control and operation based on estimated state of health (SoH) using readily available battery data. The method involves calculating estimated SoH from warranty data, rated capacity, and actual throughput. It then estimates allowable monthly throughput based on warranty, throughput, and operating months. Dynamic discharge cost is calculated using replacement cost, warranty, and throughput. Optimal discharge is determined based on estimated capacity, allowable throughput, and dynamic discharge cost. This allows optimized battery dispatch considering degradation without needing detailed characterization or access to internal parameters.

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Optimizing battery replacement strategy for power grid storage systems to minimize cost while maintaining performance. The method involves analyzing battery life factors, calculating cost-effectiveness of partial vs full replacement, and using similarity thresholds to decide between the two. This allows scientifically determining the optimal replacement strategy based on remaining battery life.

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Electric vehicle management system that considers battery degradation to optimize fleet operations. The system classifies EVs based on battery age deterioration and distance traveled deterioration. It then allocates vehicles for specific trips taking into account degradation acceleration from usage plans. This allows managing EVs based on their battery health to prevent stranded vehicles with severely degraded batteries. The system also notifies optimal parking locations for EVs with higher age deterioration to mitigate further degradation.

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