Predictive Regenerative Braking Using GPS and IMU Route Data
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Solution Overview
Problem
Hybrid/electric vehicles face challenges in determining an effective strategy for regenerative braking, particularly in predicting and applying it across various use cases, which limits their range due to limited battery capacity.
Innovation Solution
Implementing an electronic control unit that utilizes GPS and IMU data to predict and apply regenerative braking by identifying elevation points and switching the motor direction to regenerate energy, even when the brake pedal is not engaged, and monitoring driving patterns to optimize energy recovery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If regenerative braking is applied only when the brake pedal is engaged, then the control system remains simple, but energy recovery opportunities are lost and the vehicle range is limited
Solution Approach 1:
The system performs preliminary actions by using GPS and IMU sensors to predict upcoming elevation points and braking opportunities before the driver actually brakes. The controller pre-calculates optimal regenerative braking points based on route elevation data, allowing the system to prepare and execute energy recovery at the right moment without requiring complex real-time decision-making during actual braking events.
Solution Approach 2:
The system enables the vehicle to automatically identify and execute regenerative braking opportunities without continuous driver input or complex manual control. Once the driver selects a destination, the system autonomously monitors GPS position, predicts elevation changes, and automatically applies regenerative braking at optimal points, making the energy recovery process self-managing and reducing the burden on the driver while maximizing energy recovery.
2Loss of energy
If the vehicle uses traditional friction braking only, then the control strategy is simple, but kinetic energy is wasted and battery capacity is underutilized
Solution Approach 1:
The system implements feedback by continuously monitoring the vehicle's GPS position, comparing it with pre-loaded route elevation data, and using IMU sensors to detect actual braking events. This feedback loop allows the controller to determine when regenerative braking should be applied versus when friction braking is appropriate, optimizing energy recovery while maintaining safe and comfortable braking operation through adaptive control based on real-time conditions.
Solution Approach 2:
The system changes the braking parameter from purely friction-based to a hybrid approach by introducing regenerative braking as an additional mode. The controller dynamically adjusts between friction braking and regenerative braking based on predicted elevation points, vehicle speed, and driving conditions, thereby reducing kinetic energy loss while maintaining ease of operation through seamless transition between braking modes that is imperceptible to the driver.
3Productivity
If regenerative braking is predicted based on GPS and IMU data, then energy recovery is optimized, but the system requires multiple sensors and processing capabilities
Solution Approach 1:
The system achieves multi-functionality by using the GPS receiver and IMU sensors for multiple purposes: navigation, position tracking, elevation prediction, and braking event detection. The GPS data serves both route planning and regenerative braking prediction, while the IMU sensors monitor both vehicle dynamics and driver braking behavior. This universal use of sensors maximizes their utility without requiring additional dedicated components, thereby optimizing energy recovery efficiency while limiting the increase in device complexity.
Solution Approach 2:
The controller acts as an intermediary that integrates data from GPS, IMU sensors, and existing braking system information to make regenerative braking decisions. Rather than requiring direct complex interactions between multiple specialized components, the controller mediates by processing sensor inputs, comparing them with route elevation data, and generating appropriate control signals for the regenerative braking system, thereby simplifying the overall system architecture while maintaining high energy recovery efficiency.
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
Enhances the vehicle's ability to recharge while driving without user interaction, increasing the vehicle's range by effectively converting kinetic energy into electrical energy.
Implementation Method 1
Hybrid/electric vehicles may include electric circuitry configured to convert kinetic energy into electrical energy via a regenerative operation when an electrical motor is used in reverse. The electrical motor functions as a generator and converts mechanical energy into electrical energy
Data Source
AI summary
Systems and methods to predict and apply regenerative braking using GPS (global positioning system) and IMU (inertial measurement unit) data. Techniques described herein may be utilized to use a vehicle's current GPS position and IMU sensor data to determine charging availability for electric or hybrid vehicles. IMU and/or GPS data is used to determine a next path prediction and detect next route elevation level. If the next route elevation level is above a threshold, value, the vehicle's motor may be automatically swapped for regenerating energy. Accordingly, recharging operations may be performed in a wide change of scenarios, including those where a driver has not engaged the brake pedal.