EV Power Estimation Using Grouped Consumption Tendencies
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Solution Overview
Problem
Current methods for estimating the consumed power amount and runnable distance of electric vehicles (EVs) are limited, as they are specific to individual auto manufacturers and car models, and do not effectively account for external factors influencing power consumption, such as weather, road conditions, and driver behavior, making it difficult for corporations like expressway operators to manage charging and prevent battery exhaustion.
Innovation Solution
A consumed power amount estimation apparatus that uses past history data and current data to estimate power consumption, incorporating external factors by grouping similar EVs based on power consumption tendencies and reflecting knowledge about road, vehicle, and driver models, allowing for accurate estimation across multiple auto manufacturers and car models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If estimation methods are specific to individual auto manufacturers and car models, then estimation accuracy for specific vehicles is improved, but adaptability to various EV models and external factors deteriorates
Solution Approach 1:
The patent creates a universal estimation apparatus that can handle multiple EV models from different manufacturers by introducing a knowledge storage unit that stores standardized power consumption models and a knowledge extraction unit that adapts these models to specific vehicles. This allows the system to serve various EV models while maintaining accurate estimation through manufacturer-specific parameter adjustments.
Solution Approach 2:
The patent segments the estimation system into distinct functional units: a power consumption model storage unit containing standardized models, a knowledge extraction unit that processes history data, and an estimation unit that combines both. This segmentation allows the system to separately manage universal estimation algorithms and vehicle-specific adaptations, resolving the contradiction between generalizability and precision.
2Device complexity
If only internal EV information is used for estimation, then system complexity is reduced, but estimation accuracy considering external factors deteriorates
Solution Approach 1:
The patent introduces a knowledge storage unit and knowledge extraction unit as intermediary components between the estimation unit and external data sources. These intermediaries process and standardize external information (weather, road conditions, traffic) before feeding it to the estimation unit, thereby improving accuracy without significantly increasing system complexity.
3Quantity of substance
If charging stations are concentrated in limited locations, then infrastructure cost is reduced, but reliability of charging availability deteriorates
Solution Approach 1:
The patent enables preliminary estimation of consumed power amounts and runnable distances before EVs reach charging stations. By accurately predicting power consumption based on history data and current conditions, the system allows EVs to plan their routes and charging needs in advance, reducing the need for widespread charging infrastructure while ensuring reliable charging availability at strategic locations.
Data Source
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AI summary
According to an embodiment, a consumed power amount estimation apparatus includes an estimation unit (15) configured to estimate a power amount necessary for an electric vehicle having a similar power consumption tendency to run, based on a parameter used to compensate for information affecting power consumption by running of the electric vehicle based on consumed power amount information of each of a plurality of electric vehicles having similar power consumption tendencies.