Predictive Battery SOC Control for Downhill Regenerative Braking
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Solution Overview
Problem
Conventional regenerative braking systems in electrified vehicles face inefficiencies when the battery is fully charged, leading to excessive wear of friction brakes during extended downhill regions and inconsistent driving experiences due to the inability to store captured energy effectively.
Innovation Solution
A predictive energy storage management system that utilizes GPS and map data to anticipate upcoming regeneration regions, controlling electric motors to deplete the energy storage system before the region, maximizing regenerative braking and avoiding friction braking, thereby maintaining optimal battery charge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If regenerative braking is used to capture energy during downhill regions, then energy storage is improved, but when the battery is fully charged, regenerative braking cannot function and friction brakes must be used instead
Solution Approach 1:
The system performs preliminary actions by depleting the battery state of charge before entering the regeneration region through electric motor loading, ensuring the battery is ready to accept regenerative energy. This proactive energy management allows regenerative braking to function reliably throughout the entire downhill region without being constrained by full battery charge conditions.
2Quantity of substance
If the battery state of charge is maintained at full charge for optimal energy storage, then energy availability is improved, but regenerative braking cannot capture additional energy during downhill regions
Solution Approach 1:
The system dynamically adjusts the battery state of charge based on upcoming regeneration opportunities detected through GPS and map data. Rather than maintaining a static full charge state, the system optimizes SOC in real-time by depleting energy before regeneration regions and maximizing energy capture during these regions, thereby reducing energy loss while maintaining optimal energy availability.
3Ease of operation
If friction brakes are used when battery is full during extended downhill regions, then immediate braking capability is maintained, but brake wear increases excessively
Solution Approach 1:
The system replaces mechanical friction braking with electric motor-based regenerative braking by dynamically managing battery state of charge. Electric motors operate in generating mode during downhill regions to provide braking force while simultaneously charging the battery, eliminating the need for friction brake usage and thereby extending brake lifespan while maintaining responsive braking control.
4Productivity
If the energy storage system is depleted before the regeneration region, then regenerative braking efficiency is maximized, but the vehicle requires additional energy management control
Solution Approach 1:
The system employs feedback mechanisms by continuously monitoring battery state of charge, vehicle speed, acceleration, and GPS location to dynamically control electric motor operation. This feedback loop enables the system to automatically deplete energy before regeneration regions and maximize energy capture during these regions, achieving high regenerative energy capture while managing control complexity through intelligent 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 approach optimizes energy storage by proactively managing battery levels, reducing brake wear and providing a consistent driving experience by fully utilizing regenerative braking, potentially reducing vehicle costs and improving consumer satisfaction.
Implementation Method 1
the regenerative braking system to recharge the energy storage system to a desired level during and by the end of the regeneration region
Implementation Method 2
the controller controls one or more electric motors of an electrified powertrain of the electrified vehicle to intentionally deplete the energy storage system
Data Source
AI summary
Predictive energy storage management techniques for an electrified vehicle obtaining a set of global positioning satellite (GPS) and map data and, based on the set of GPS and map data, detect an upcoming regeneration region that the electrified vehicle will encounter, predict a regenerative energy that a regenerative braking system of the electrified vehicle can generate across the regeneration region, determine a target stored energy for the energy storage system of the electrified vehicle based on the predicted regenerative energy, control one or more electric motors of an electrified powertrain of the electrified vehicle to intentionally deplete the energy storage system to the target stored energy by the start of the regeneration region, and control the regenerative braking system to recharge the energy storage system to a desired level during and by the end of the regeneration region.