Dr.EV

Icon for Dr.EV
Installs

2.2k

Rating

0.0

Rating count

< 100

CategoryAuto & Vehicles
Developer(주)배러머신
PriceFree
First release4/19/2024 (last year)
Version2.1.79
In-app purchasesNo
Contains adsNo
Content ratingEveryone
Package namecom.battermachine.drev

View on Play Store

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Core Metrics

Data Breakdown

DateRating CountAverage RatingInstallsVersion
6/12/202500.0002,1922.1.79
6/9/202500.0002,1862.1.76
6/8/2025264.7142,176N/A
5/29/2025264.7142,173N/A
5/28/2025254.7002,111N/A
5/27/2025254.7002,103N/A
5/24/2025254.7002,100N/A
5/22/2025264.7002,084N/A
5/21/2025264.7002,078N/A
5/20/2025264.7002,053N/A
5/19/2025264.7002,037N/A
4/24/2025224.8891,803N/A
4/22/2025214.9411,786N/A
4/15/2025214.9411,783N/A
4/10/2025184.9291,736N/A
4/6/2025154.9091,666N/A

Details

Dr.EV is your intelligent companion for optimizing Tesla battery performance and longevity. Our innovative app is designed to keep you informed and in control of your Tesla’s battery health, driving habits, and charging efficiency. Harnessing the power of cutting-edge AI, Dr.EV provides real-time Tesla Battery Management analysis, delivering precise health reports with easy-to-understand metrics such as State of Charge (SoC), Expected Range, and Overall Battery Health Percentage. Our advanced diagnostic tools detect anomalies, predict State of Health (SoH), and offer actionable insights to enhance battery efficiency and lifespan. With Dr.EV, you no longer have to worry about battery management. Our intelligent system guides you on optimal driving and charging strategies, ensuring maximum performance and durability—so you can focus on the road while we take care of your battery. Powered by Innovation: Dr.EV is built on proprietary AI algorithms and patented battery analytics. Our research has been featured in leading scientific journals and industry conferences. Learn more about our technology → https://www.sciencedirect.com/science/article/pii/S2666546823000915 Key Features of Dr.EV 🚀 🔋 Battery Health Prediction – Accurately assess and predict your EV battery's state of health (SoH) for optimal performance. 📊 Battery Management Score – Get a personalized score based on your driving and charging habits, reflecting their impact on battery life. Identify behaviors that may accelerate battery degradation and receive recommendations for improvement. 🚗 Predictive Driving Range – Receive personalized predictions for how far you can drive under specific conditions, helping you plan efficiently. ⚡ Battery Degradation Analysis – Monitor battery wear over time and receive insights on how to extend its lifespan. 🔄 Driving Energy Efficiency – Understand your driving patterns and optimize energy consumption for maximum efficiency. 🌍 CO₂ Reduction Analysis – Track your contribution to reducing carbon emissions and driving sustainability. 🔌 Charging Efficiency Analysis – Evaluate the efficiency of different chargers and charging patterns to improve battery longevity. Experience the future of EV care with Dr.EV – Smart, Simple, and Efficient. [Domestic Patents] Method and apparatus for performing high-speed charging and maximum discharge while reducing battery deterioration in electric vehicles (10-1998069-00-00) Battery monitoring and protection system (10-1912615-00-00) Apparatus and method for preventing fire occurrence in a device (10-1648749-00-00) Method and apparatus for blocking operating standby power and communication standby power in a device (10-1648746-00-00) Method and apparatus for detecting devices operating abnormally compared to other devices (10-1576433-00-00) [International (PCT) Applications] Method for labeling training data of a deep neural network model for battery state estimation and a learning method using the same (PCT/KR2024/018582) Method for labeling training data of a deep neural network model for battery remaining life estimation (PCT/KR2024/018588) Method and apparatus for generating a safe-DNN model to safely estimate the battery state (PTC/KR2024/018879) Method for generating a DNN model for battery state estimation accommodating multivariate input vectors (PCT/KR2024/018938) Method for generating a learning model for battery state estimation through conditional learning (PCT/KR2024/018929) Method for generating a battery state estimation learning model by applying different types of DNN according to the battery life cycle (PCT/KR2024/018956) Method for estimating SOH during battery discharge using limited data (PCT/KR2024/019086) Method for estimating SOH during battery charging using limited data (PCT/KR2024/019107) Method for improving the reliability of SOH/RUL estimation through SOH filtering (PCT/KR2024/019132) (Some patents are omitted due to space limitations.)

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