Hybrid Vehicle Engine Control for EV Mode Optimization
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Solution Overview
Problem
Electric vehicles (EVs) face inefficiencies in maintaining EV mode near destinations due to unpredictable battery state of charge and driver demands, leading to unnecessary engine start-ups, which affect fuel economy and driver satisfaction.
Innovation Solution
A vehicle system that determines the current location and adjusts engine pull-up characteristics, such as increasing the EV threshold or decreasing the state of charge threshold, based on the distance and score of nearby waypoints associated with past ignition-off events, to optimize EV mode driving by predicting future ignition-off events and managing battery usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If the engine is started to ensure sufficient power supply near destinations, then driver demands are met, but fuel economy deteriorates due to unnecessary engine start-ups
Solution Approach 1:
The system performs preliminary actions by learning and storing destination locations from historical ignition-off events before the vehicle actually reaches them. This advance knowledge allows the control system to predict when the vehicle will stop and pre-adjust engine start-up characteristics, preventing unnecessary engine start-ups while ensuring power is available when truly needed.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring driver demands, battery state of charge, and vehicle location relative to learned destinations. This feedback loop enables dynamic adjustment of engine pull-up characteristics, allowing the system to respond appropriately to actual conditions rather than using fixed thresholds, thereby optimizing both power availability and fuel economy.
2Loss of energy
If the EV threshold is increased to maintain EV mode near destinations, then fuel economy improves, but driver satisfaction deteriorates due to insufficient power response
Solution Approach 1:
The system applies dynamics by making the EV threshold and engine pull-up characteristics variable rather than fixed. The control system dynamically adjusts these parameters based on real-time conditions including vehicle location relative to learned destinations, battery state of charge, and driver demand patterns. This dynamic adjustment allows the system to maintain high EV thresholds for fuel economy while providing immediate engine response when drivers actually need power.
3Loss of energy
If the engine pull-up characteristic is adjusted based on location and historical data, then fuel economy improves by reducing unnecessary start-ups, but device complexity increases
Solution Approach 1:
The system implements self-service by automatically learning destination locations from historical ignition-off events without requiring manual driver input or complex configuration. The control system autonomously builds and updates the destination database, performs location matching, and adjusts engine characteristics based on this learned information, thereby achieving sophisticated fuel economy optimization without proportionally increasing operational complexity.
Data Source
AI summary
Location information may be used to adjust the engine start/stop characteristics of a hybrid electric vehicle (HEV) in order to increase the amount of electric vehicle (EV) mode driving, particularly near a destination in which an ignition-off event may occur. Common ignition-off locations may be learned and stored in a database along with the number of ignition-off occurrences associated with each learned location. The vehicle may calculate current distance to a nearest ignition-off location stored in the database using positioning system coordinates and may determine whether to adjust one or more engine pull-ups based at least in part on the distance and the corresponding number of ignition-off occurrences.