Navigation-Based Regenerative Braking Torque Control in EVs
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Solution Overview
Problem
Hybrid and electric vehicles face challenges in optimizing regenerative braking torque based on varying driving scenarios, such as speed limits, road conditions, and external factors like weather and traffic, which affects energy efficiency and driver assistance systems.
Innovation Solution
A vehicle control system that includes an electric machine, sensors, a receiver, and an electronic horizon module, programmed to adjust regenerative braking torque dynamically based on route attribute data, external conditions, and navigation data, distinguishing between different driving scenarios to optimize torque levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If regenerative braking torque is increased to maximize energy recovery, then energy efficiency is improved, but driver comfort and vehicle control are worsened under certain driving conditions
Solution Approach 1:
The control system dynamically adjusts regenerative braking torque based on real-time driving conditions, vehicle state, and environmental factors. The torque magnitude is not fixed but varies continuously according to the situation, allowing the system to optimize energy recovery while maintaining driver comfort and vehicle controllability under different operating conditions.
Solution Approach 2:
The system changes multiple parameters simultaneously including torque magnitude, braking pressure, and control strategy based on detected conditions. By adjusting these parameters according to driving scenario, road grade, weather conditions, and traffic situation, the system resolves the contradiction between maximizing energy recovery and maintaining acceptable driving comfort.
2Loss of energy
If regenerative braking torque is increased for all stopping scenarios, then energy recovery is improved, but vehicle control and safety are worsened in certain conditions
Solution Approach 1:
The control system dynamically evaluates multiple factors including road grade, weather conditions, traffic situation, and vehicle state to determine the appropriate regenerative braking torque. This dynamic adjustment ensures that energy recovery is maximized only when safe and appropriate, while maintaining vehicle control and safety under all conditions.
Solution Approach 2:
The system performs preliminary assessment of driving conditions and vehicle state before applying regenerative braking torque. By evaluating road grade, weather, traffic, and battery state in advance, the system determines the optimal torque level that balances energy recovery with vehicle control and safety requirements.
3Ease of operation
If regenerative braking torque is reduced for comfort, then driver assistance is improved, but energy efficiency is worsened
Solution Approach 1:
The control system dynamically adjusts torque based on the specific driving scenario. In situations where maximum energy recovery is beneficial and safe (such as downhill driving or when battery charge is needed), the system applies higher torque. In situations where driver comfort is prioritized (such as light braking or when battery is fully charged), the system reduces torque accordingly.
Solution Approach 2:
The system changes torque parameters based on multiple input factors including accelerator pedal position, brake pedal position, vehicle speed, road grade, and battery state of charge. This multi-parameter adjustment allows the system to optimize the balance between driver assistance and energy efficiency for each specific driving condition.
4Use of energy by moving object
If the control system considers multiple driving scenarios and external conditions, then energy efficiency is improved, but system complexity is worsened
Solution Approach 1:
The control system is designed to perform multiple functions using a single integrated controller. It simultaneously monitors driving conditions, evaluates battery state, determines optimal torque levels, and adjusts regenerative braking across different operating scenarios. This multi-functional approach consolidates complexity into a single system rather than requiring separate systems for each function.
Solution Approach 2:
The system continuously receives feedback from multiple sensors monitoring vehicle state, environmental conditions, and battery charge level. This feedback loop allows the controller to dynamically adjust regenerative braking torque in real-time based on actual conditions, optimizing energy efficiency without requiring complex manual intervention or multiple separate control systems.
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 energy efficiency and improves driver assistance by dynamically adjusting regenerative braking torque in response to changing driving conditions, ensuring optimal vehicle control and fuel economy.
Implementation Method 1
The electric machine is configured to propel the vehicle and to brake the vehicle via regenerative braking
Data Source
AI summary
A vehicle includes an electric machine and a controller. The controller is programmed to, in response to releasing an accelerator pedal during a first driving scenario that is based on a first set of navigation data, increase regenerative braking torque of the electric machine to a first value. The controller is further programmed to, in response to releasing the accelerator pedal during a second driving scenario that is based on a second set of navigation data, increase the regenerative braking torque of the electric machine to a second value that is less than the first value.