Electric Efficiency Prediction Using Vehicle Status Correction
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Solution Overview
Problem
Existing methods for predicting electric efficiency in electric vehicles do not accurately account for factors other than vehicle type, leading to inaccuracies in estimating power consumption per unit traveling distance.
Innovation Solution
An electric efficiency prediction method that corrects actual electric efficiency values using object vehicle information such as load amount, air conditioner operation state, driving tendency, and environmental conditions to calculate a predicted value for each link on the expected traveling route, providing location information about nearby charging facilities when the state of charge falls below a threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If electric efficiency is calculated based only on vehicle type information, then the calculation process is simple, but the prediction accuracy is insufficient
Solution Approach 1:
The patent introduces multiple correction parameters (load amount, air conditioner operation state, driving tendency) to modify the base electric efficiency value. By changing the parameters used in calculation from a single vehicle type parameter to multiple operational parameters, the prediction accuracy is improved while maintaining a structured calculation approach.
Solution Approach 2:
The calculation process is segmented into distinct correction steps: base efficiency calculation from vehicle type, then sequential corrections for load amount, air conditioner state, and driving tendency. This segmentation allows the complex prediction process to be broken down into manageable components that can be applied systematically.
2Measurement precision
If multiple vehicle status parameters are used to correct electric efficiency values, then prediction accuracy is improved, but the data processing complexity increases
Solution Approach 1:
The patent performs preliminary corrections in a predetermined sequence: first correcting for load amount, then air conditioner operation state, and finally driving tendency. This preliminary action approach organizes the complex data processing into a systematic sequence, making the multi-parameter correction process more manageable and computationally efficient.
Solution Approach 2:
The system uses collected actual electric efficiency data from multiple vehicles to continuously refine and update the correction values for each parameter. This feedback mechanism allows the system to learn from real-world data and improve prediction accuracy over time while adapting to varying operational conditions.
Data Source
AI summary
An electric efficiency prediction method for a vehicle includes: the first step of obtaining “object vehicle information” showing information about a status of use of a vehicle that is an electrically powered vehicle; and the second step of, for each link connecting nodes virtually set on an expected traveling route of the vehicle, by using the object vehicle information, correcting an electric efficiency actual value of electric efficiency collected from each of a plurality of vehicles to calculate an electric efficiency predicted value in each link for the vehicle.