Hybrid Vehicle Control System for Low Emission Area EV Mode
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Solution Overview
Problem
Hybrid vehicles face limitations in maintaining electric vehicle mode in low emission areas due to battery capacity and regenerative control frequency, leading to excessive battery SOC depletion and potential engine operation.
Innovation Solution
A control system and method for hybrid vehicles that includes an on-board learning unit and a server learning unit, which determine the vehicle's location in low emission areas and adjust learning actions to conserve battery power, such as partially or fully stopping learning actions when in low emission areas to maintain EV mode.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If regenerative control is performed frequently to increase battery SOC before entering low emission area, then battery SOC can be maintained higher, but there is a limit to increasing SOC due to battery capacity and the SOC may become excessively low in the specific area
Solution Approach 1:
The system performs preliminary regenerative control before the hybrid vehicle enters a low emission area to increase battery SOC in advance. The control determination unit identifies upcoming low emission areas using map data and performs regenerative control operations beforehand, so that sufficient electric power is available when entering the restricted area, ensuring EV mode can be maintained throughout.
Solution Approach 2:
The control determination unit continuously monitors battery SOC levels and compares them against threshold values. Based on this feedback, the system dynamically adjusts regenerative control intensity and timing. When SOC is predicted to be insufficient before entering a low emission area, the system intensifies regenerative braking to recharge the battery, ensuring adequate power availability for EV mode operation in the restricted zone.
2Measurement precision
If on-board learning unit operates continuously to improve vehicle control, then learning accuracy improves, but power consumption increases which depletes battery SOC
Solution Approach 1:
The learning control unit dynamically adjusts the operation of the on-board learning unit based on real-time conditions. When the hybrid vehicle is in EV mode or approaching low emission areas, the system reduces or suspends on-board learning operations to minimize power consumption. When outside restricted zones or in HV mode with sufficient battery charge, the system resumes learning operations to maintain model accuracy without compromising EV mode sustainability.
Solution Approach 2:
The system applies different learning control strategies in different spatial contexts. In low emission areas and adjacent zones where EV mode is critical, on-board learning is suspended or reduced. In other areas where the vehicle can operate in HV mode, full learning operations are permitted. This localized quality adjustment ensures learning accuracy is maintained where possible without interfering with emission compliance.
3Quantity of substance
If learning action is stopped in low emission area to conserve power, then battery SOC is preserved for EV mode, but learning accuracy may deteriorate
Solution Approach 1:
The system introduces map data and position information as intermediary elements to coordinate between learning operations and emission area constraints. The control determination unit uses geographic information to identify low emission areas and their boundaries, then uses this information to strategically suspend on-board learning only when necessary. This intermediary approach allows the system to maintain learning accuracy in non-restricted areas while preserving battery SOC for EV mode operation in restricted zones.
Solution Approach 2:
The on-board learning unit operates periodically rather than continuously, with operation cycles adjusted based on location and battery status. When approaching or entering low emission areas, learning operations are temporarily suspended. After exiting these areas, learning resumes. This periodic action pattern allows the system to maintain adequate learning accuracy over time while ensuring battery SOC is preserved during critical EV mode operation in emission-restricted zones.
Data Source
AI summary
A control system for a hybrid vehicle which includes an internal combustion engine and an electric motor and whose drive mode is switchable between an electric vehicle mode and a hybrid vehicle mode includes: an on-board learning unit mounted on the hybrid vehicle and configured to perform a learning action; a position determination unit configured to determine whether the hybrid vehicle is located in a low emission area where operation of the internal combustion engine is supposed to be restricted; and a learning control unit configured to at least partially stop the learning action of the on-board learning unit when determination is made that the hybrid vehicle is located in the low emission area.