Regenerative Braking Detection for Cross-Vehicle Driver Assessment
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Solution Overview
Problem
Existing methods for assessing and advising drivers of electric or hybrid vehicles on regenerative braking are not adaptable to different vehicle specifications, limiting their effectiveness in maximizing energy efficiency.
Innovation Solution
A computer-implemented method and system that detects deceleration events in a data gathering vehicle, obtains and timestamps data on power, speed, and acceleration, generates a function representing their relationship, and applies this function to determine if mechanical braking is used, adaptable to vehicles of varying specifications by using data from similar vehicles within a fleet.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing assessment methods are used for individual vehicles with fixed vehicle information, then the assessment is simple to implement, but the adaptability to different vehicle specifications is poor
Solution Approach 1:
The patent creates a universal assessment method that can be applied across multiple vehicle types and specifications. By using a standardized data collection framework and generic machine learning model training process, the system achieves multi-functionality across different electric and hybrid vehicles without requiring vehicle-specific customization, thus improving adaptability while maintaining manageable complexity
Solution Approach 2:
The patent performs preliminary data collection during a data gathering phase before the actual assessment begins. By collecting and storing vehicle data in advance, and pre-training machine learning models on this data, the system prepares adaptable assessment capabilities beforehand, allowing the assessment to be applied to different vehicle specifications without complex real-time adjustments
2Use of energy by moving object
If regenerative braking is maximized and friction braking is minimized, then energy efficiency is improved, but the ability to assess and advise drivers accurately is reduced without adaptable methods
Solution Approach 1:
The patent implements a feedback mechanism where machine learning models analyze driver behavior data from regenerative braking events and provide assessments and advice to drivers. This feedback loop enables accurate measurement of driver performance in maximizing regenerative braking, with the precision improved through adaptable models that learn from actual vehicle data rather than relying on fixed thresholds
Solution Approach 2:
The patent uses machine learning models that can adapt to different vehicle parameters and specifications. By training models on vehicle-specific data and allowing them to learn optimal regenerative braking patterns for different vehicle types, the system achieves precise assessment across varying parameters while promoting energy-efficient driving behavior
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables efficient assessment and advice on regenerative braking across vehicles with different specifications, improving energy efficiency by minimizing mechanical braking and maximizing regenerative braking usage.
Implementation Method 1
The drive motor being turned by the momentum of the vehicle induces a current which can be used to charge the battery for powering the electrical drive unit (traction battery)
Data Source
AI summary
A computer-implemented method (100) of assessing and/or advising a driver of an electric or hybrid vehicle (1), the method comprising: detecting a series of deceleration events of a data gathering vehicle (1a); during each detected deceleration event, obtaining data indicative of: a power provided to the battery (5) by the regenerative braking system (3), vehicle speed, and vehicle acceleration; and generating a function representing a relationship between the power provided to the battery (5) by the regenerative braking system (3), the speed, and the acceleration; detecting a deceleration event of a monitored vehicle (1b); obtaining data indicative of: a power provided to the battery (5) by the regenerative braking system (3), vehicle speed, and vehicle acceleration; and using the generated function, and the time stamped monitoring data obtained during said deceleration event, to determine whether a driver of the monitored vehicle (1b) has used mechanical braking.