EV Regenerative Braking Torque Prediction for Energy Recovery
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Solution Overview
Problem
The inability to accurately determine an optimal motor feedback torque for energy recovery in electric vehicles affects the efficiency of energy recovery during braking and coasting, leading to suboptimal energy conservation and consumption reduction.
Innovation Solution
An energy recovery method that acquires vehicle traveling information, including road condition and status information, to predict a motor braking feedback torque, allowing for precise energy recovery based on calculated braking demands and battery pulse charging characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If motor feedback torque is increased to improve energy recovery, then energy recovery efficiency is improved, but the accuracy of determining optimal feedback torque deteriorates
Solution Approach 1:
The system performs preliminary prediction of motor braking feedback using a prediction model that takes vehicle traveling information as input. This preliminary action determines the optimal feedback torque before actual braking occurs, allowing the system to achieve both high energy recovery efficiency and accurate torque determination by pre-calculating the optimal values based on predicted braking demands
Solution Approach 2:
The system implements a feedback mechanism where the predicted motor braking feedback is used to adjust and optimize the actual braking torque applied. This feedback loop ensures that the motor operates at optimal feedback torque levels for energy recovery while maintaining accurate control through continuous monitoring and adjustment based on actual vehicle conditions
2Loss of energy
If predictive calculation is used to improve energy recovery accuracy, then energy recovery efficiency is improved, but computational complexity increases
Solution Approach 1:
The prediction model operates autonomously using vehicle traveling information already available in the system. It self-determines the optimal motor braking feedback without requiring complex external computational resources, achieving accurate predictive calculations while maintaining relatively simple system architecture by utilizing existing data and self-contained algorithms
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
This method enhances energy recovery efficiency by optimizing motor braking feedback, reducing energy loss through predictive calculations and advanced battery charging strategies, thereby improving the overall energy conservation and utilization in electric vehicles.
Implementation Method 1
a motor performs braking when a driver depresses a brake pedal... performing energy recovery according to the first motor braking feedback
Data Source
AI summary
An energy recovery method and device, an electric vehicle, and a storage medium are provided. The energy recovery method includes: acquiring vehicle travelling information, wherein the vehicle travelling information comprises road condition information and travelling status information; acquiring a vehicle braking demand according to the road condition information and the travelling status information; predicting a first motor braking feedback according to the vehicle braking demand; and performing energy recovery according to the first motor braking feedback.