Dynamic EV Battery Recommendation System for Weight Optimization
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Solution Overview
Problem
Conventional battery selection models for electric vehicles result in inefficient energy storage and increased weight, as they are sized to exceed typical driving ranges to alleviate range anxiety, leading to suboptimal energy storage capacity and unnecessary weight.
Innovation Solution
A vehicle battery recommendation system that uses sensors and modules to detect driver behavior and vehicle consumption patterns to determine an optimal battery replacement option that modifies characteristics such as specific energy, weight, and charging rate, optimizing battery capacity based on individual driving habits and needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If battery size and weight are increased to meet peak range expectations and alleviate range anxiety, then the vehicle can satisfy a wider range of driving distances and reduce occurrences of running out of energy, but the overall vehicle weight increases and energy consumption increases
Solution Approach 1:
The patent implements a dynamic battery recommendation system that adapts battery selection to actual driving conditions, driver behavior patterns, and environmental factors. The system dynamically adjusts battery capacity recommendations based on real-time data from sensors monitoring driving habits, route information, weather conditions, and historical consumption patterns, rather than relying on static peak-range specifications.
Solution Approach 2:
The system changes the parameter of battery capacity selection from fixed peak-range-based sizing to variable sizing based on multiple factors including driver behavior classification (aggressive/conservative), route characteristics, weather conditions, and historical energy consumption data. This allows optimization of battery parameters for specific usage scenarios rather than designing for maximum possible range.
2Adaptability or versatility
If battery size and weight are increased to meet peak range expectations, then the vehicle can satisfy a wider range of driving distances, but the energy storage efficiency decreases due to suboptimal capacity utilization
Solution Approach 1:
The system performs preliminary analysis of driver behavior patterns, route characteristics, and historical consumption data before making battery recommendations. By pre-classifying drivers into behavior types and pre-calculating optimal battery capacities based on various scenario combinations, the system can quickly provide accurate recommendations without requiring real-time complex computations during vehicle operation.
Solution Approach 2:
The system incorporates feedback loops that continuously monitor actual energy consumption, compare it with predicted consumption, and refine battery recommendations over time. Historical data from multiple driving cycles is fed back into the model to improve accuracy of consumption predictions and optimize battery capacity suggestions for different driver profiles and usage patterns.
3Adaptability or versatility
If a larger battery is installed to maximize market appeal and satisfy diverse driving needs, then more drivers are accommodated, but the vehicle weight increases leading to higher energy consumption
Solution Approach 1:
The patent applies local quality by providing customized battery recommendations tailored to specific driver profiles, routes, and usage patterns rather than a one-size-fits-all approach. The system identifies specific segments of drivers (e.g., conservative drivers with short commutes, aggressive drivers with long trips) and recommends appropriate battery capacities for each segment, allowing manufacturers to offer optimized configurations for different market segments.
Data Source
AI summary
An optimal vehicle battery recommendation system includes at least one sensor to detect a manipulation of the vehicle. A driver behavior module determines a driving behavior of a driver of the vehicle. A vehicle consumption module determines battery information of an on-board battery currently connected to the vehicle, and determines energy consumption of the vehicle. A battery capacity advisor module is in electrical communication with the driver behavior module and the vehicle consumption module. The battery capacity module determines a replacement battery option that changes at least one battery characteristic of the on-board battery based on the driver behavior model and the vehicle consumption model.