EV Battery SOC Targeting for Regenerative Braking Reserve
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Solution Overview
Problem
Electric vehicles face challenges in optimizing battery state of charge (SOC) for regenerative braking, especially when the upcoming route's gradient profile is unknown or uncertain, leading to inefficient energy management and reduced vehicle range.
Innovation Solution
A method that determines a target SOC for an electric vehicle's battery by estimating the worst-case predicted total energy consumption based on an estimated gradient profile and adjusts this target SOC using a confidence factor associated with the estimation accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the battery is charged to maximum SOC, then the energy storage capacity is maximized, but the regenerative braking capacity is reduced
Solution Approach 1:
The patent applies dynamics by making the target SOC adjustable and adaptive rather than fixed. The system dynamically determines the optimal target SOC based on real-time gradient profile predictions, vehicle energy consumption characteristics, and environmental conditions. This allows the battery charge level to be optimized for each specific driving scenario, balancing energy storage needs with regenerative braking requirements
Solution Approach 2:
The patent changes the SOC parameter based on different gradient profiles and driving conditions. Instead of maintaining a constant maximum SOC, the system adjusts the target SOC parameter dynamically - charging to lower levels when steep descents are predicted (to preserve regenerative braking capacity) and higher levels when gentle terrain is expected (to maximize energy storage). This parameter adaptation resolves the contradiction between storage and braking capacity
2Device complexity
If the target SOC is determined without gradient information, then the charging process is simpler, but the energy management accuracy is reduced
Solution Approach 1:
The patent applies preliminary action by obtaining gradient profile information before determining the target SOC. The system proactively retrieves topographic data, route information, and environmental conditions in advance of the charging decision. This preliminary gathering of gradient information enables more accurate energy consumption predictions and better-optimized target SOC selection, improving energy management accuracy without adding significant operational complexity
Solution Approach 2:
The patent introduces gradient profile data as an intermediary element that mediates between the charging system and the vehicle's energy needs. This intermediary information layer - consisting of predicted gradient profiles, altitude changes, and route characteristics - enables the charging controller to make informed decisions about target SOC without requiring complex real-time monitoring during charging. The gradient data acts as a predictive mediator that simplifies the control process while enhancing accuracy
Data Source
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AI summary
A battery control component of an electric vehicle may limit charging of a battery on the electric vehicle to a target state of charge (SOC), such as to reserve battery capacity for regenerative braking during downgrades. A computing device associated with the vehicle may calculate an estimated gradient profile and/or an estimated total energy consumption of a predicted upcoming route of the vehicle based on one or more data items, such as GPS data, altitude data, and/or map data. The computing device may determine a target SOC based on the estimated gradient profile. The computing device may determine a confidence factor associated with the estimated gradient profile, where the confidence factor depends on the quantity of data items used to calculate the estimated gradient profile. The computing device may adjust the target SOC based on the confidence factor.