Regenerative Coasting Control Using Environmental Artifact Prediction
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Solution Overview
Problem
Conventional electrified vehicles do not effectively consider environmental artifacts during regenerative braking, leading to inefficient coast down conditions that require driver intervention.
Innovation Solution
A system and method that utilizes sensors to gather dynamic and static environmental data to determine optimal deceleration rates, adjusting regenerative braking based on artifacts like moving objects and road signs, ensuring smooth coast down and efficient energy recovery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If conventional regenerative braking applies minimum torque as a function of vehicle velocity, then energy recovery is achieved, but the vehicle does not consider surrounding artifacts leading to inefficient coast down conditions requiring driver intervention
Solution Approach 1:
The system performs preliminary actions by using sensors to detect artifacts (traffic signs, road conditions, other vehicles) ahead of time and pre-calculating the optimal deceleration profile. This allows the vehicle to automatically adjust regenerative braking torque before the driver would need to intervene, maintaining energy efficiency while eliminating the need for driver input.
Solution Approach 2:
The system implements feedback by continuously monitoring environmental artifacts and vehicle state, then adjusting the regenerative braking torque in real-time. The controller receives sensor data about surrounding conditions and feeds this information back to modify the deceleration rate, ensuring the vehicle responds appropriately to environmental factors without driver intervention.
2Loss of energy
If the vehicle coasts during regenerative braking without considering environmental artifacts, then energy recovery occurs, but the deceleration may be insufficient when artifacts ahead require the vehicle to slow down more
Solution Approach 1:
The system applies dynamics by making the regenerative braking torque adjustable and adaptive rather than fixed. The controller dynamically modifies the deceleration rate based on detected artifacts and predicted driving scenarios, allowing the vehicle to transition between coasting (for energy recovery) and active deceleration (when artifacts require it) seamlessly.
Solution Approach 2:
The control system acts as an intermediary between the regenerative braking system and environmental conditions. It processes sensor data about artifacts and translates this information into appropriate torque adjustments, mediating between the need for energy recovery and the need to respond to environmental factors requiring additional deceleration.
3Ease of operation
If the vehicle increases deceleration to respond to environmental artifacts, then driveability improves, but energy efficiency may be reduced due to increased braking torque
Solution Approach 1:
The system changes parameters by adjusting the regenerative braking torque level based on detected artifacts and predicted scenarios. Rather than using fixed torque values, the controller modifies electrical parameters (torque, power) dynamically to optimize both driveability and energy efficiency for each specific driving condition.
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 driveability and energy efficiency by intelligently modulating regenerative braking to match the vehicle's deceleration with environmental conditions, optimizing coast down without driver input.
Implementation Method 1
the electric motor further providing regenerative braking energy to a battery system during a deceleration event
Implementation Method 2
The first sensor comprises one of a camera and radar that senses a moving object
Implementation Method 3
The second sensor comprises a global positioning system (GPS) that provides data indicative of a road sign, an intersection, a road slop and road form
Data Source
AI summary
A system that implements a dynamically adjusting coasting regeneration for an electrified vehicle includes an electrified powertrain, first and second sensors and a controller. The electrified powertrain includes an electric motor that provides drive torque to a driveline. The first sensor senses dynamic artifact data. The second sensor senses one of static and pseudo-static artifact data. The controller is configured to receive a current velocity of the vehicle; determine first and second candidate deceleration rates based on the data; estimate a first proposed change in velocity over a first time based on the first and second deceleration rates; determine a second proposed change in velocity over a second time based on the first proposed change in velocity; determine a proposed total distance travelled by the vehicle based on the second proposed change in velocity; and determine whether a target velocity has been reached based on the proposed total distance.