Vehicle Range Estimation Using Time-of-Day Energy Patterns
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Solution Overview
Problem
There is a need for improved methods and systems to estimate the range of electric vehicles with rechargeable energy storage systems (RESS) accurately, as existing solutions do not effectively account for time-of-day variations in energy usage.
Innovation Solution
A method and system that utilize a processor and sensor unit to measure input values from the RESS, determine the available energy, and estimate the vehicle range based on the time of day, using a clock to obtain the current time and sensors to measure temperature and mileage, which allows for accurate range estimation by referencing historical energy usage patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional range estimation methods are used, then the estimation process is simple, but the accuracy of range estimation is insufficient because time-of-day variations in energy usage are not accounted for
Solution Approach 1:
The system performs preliminary actions by collecting and storing energy usage data during different time periods in advance. The processor accumulates usage data from sensors over multiple drive cycles, organizing it by time of day before需要进行范围估算。This preliminary data collection and organization enables more accurate range estimation without adding complex real-time processing requirements.
Solution Approach 2:
The system implements feedback by continuously monitoring actual energy usage through sensors and comparing it with the range estimation model. The processor uses this feedback from actual usage patterns to refine and update the range estimation, creating a closed-loop system that improves accuracy over time while maintaining manageable complexity.
2Ease of operation
If time-specific energy usage patterns are incorporated into range estimation, then the usability for drivers is improved, but the complexity of data collection and processing increases
Solution Approach 1:
The system practices self-service by automatically collecting usage data through integrated sensors and autonomously processing this data to generate time-specific range estimates. The processor independently analyzes the collected data and updates the estimation model without requiring manual driver input or intervention, thereby improving usability while keeping the system architecture relatively simple.
Solution Approach 2:
The estimation system exhibits multi-functionality by serving multiple purposes: it collects usage data for analysis, generates accurate time-specific range estimates, and provides this information to drivers in a user-friendly manner. This universal approach allows a single integrated system to handle data collection, processing, and presentation, reducing overall system complexity while enhancing driver usability.
Data Source
AI summary
Methods, systems, and vehicles are provided that provide for estimating a range of a vehicle with a rechargeable energy storage system (RESS). A sensor unit is configured to measure one or more input values pertaining to the RESS. A processor is coupled to the sensor unit, and is configured to determine an amount of energy available from the RESS using the input values and to obtain a time of day. An estimate of the range for the vehicle is determined based on the time of day and the amount of energy available.