Adaptive Hybrid Vehicle Control System for Load-Dependent Energy Distribution
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Solution Overview
Problem
Hybrid vehicles often inefficiently manage fuel consumption under varying load conditions, either burning too much fuel under light loads or relying excessively on electric drive under heavy loads, due to a lack of adaptive control schemes that account for specific operational conditions.
Innovation Solution
A system that records and classifies historical load data to assign appropriate control curves for regulating energy distribution between the internal combustion engine and electric drive, optimizing energy use based on load categories to enhance performance and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a fixed control scheme is used in hybrid vehicles, then the control system is simple to implement, but fuel efficiency deteriorates under varying load conditions
Solution Approach 1:
The control scheme transitions from a fixed static configuration to a dynamic adaptive system that automatically adjusts control parameters based on real-time load conditions. The system monitors vehicle operation and modifies the blend between internal combustion engine and electric drive propulsion according to actual demand, optimizing fuel efficiency across varying operating conditions without requiring complex manual tuning.
Solution Approach 2:
The system changes control parameters dynamically based on load conditions. By monitoring operational parameters and adjusting the propulsion mix accordingly, the system optimizes fuel consumption under light loads while ensuring adequate performance under heavy loads, resolving the contradiction between simple fixed control and efficient adaptive control.
2Use of energy by moving object
If reliance is placed on electric drive under heavy load conditions, then fuel consumption is reduced, but vehicle performance becomes deficient
Solution Approach 1:
The control system dynamically adjusts the proportion of electric drive and internal combustion engine output based on detected load conditions. Under heavy load conditions, the system increases internal combustion engine contribution to maintain required power levels, while under light load conditions, it increases electric drive contribution to reduce fuel consumption, thus optimizing both performance and energy efficiency across the operating range.
3Power
If the control scheme is tuned for specific load conditions, then performance under those conditions improves, but adaptability to varying conditions deteriorates
Solution Approach 1:
The system employs dynamic adaptation mechanisms that automatically adjust control parameters in response to changing load conditions. Rather than being optimized for a single fixed operating point, the control scheme continuously monitors vehicle operation and modifies the propulsion blend accordingly, maintaining optimal performance across diverse and varying load conditions without requiring manual retuning.
Data Source
AI summary
A method and system for adaptively controlling a hybrid vehicle comprises a recorder for recording a historical load or duty cycle of vehicle during or after operation of the vehicle. A classifier classifies the historical load in accordance with a load category. A controller assigns at least one of a current control curve and a slew rate control curve associated with the load category for a defined time period after the recording of the historical load or if the vehicle is presently operating generally consistent with the load category. At least one of the current control curve and the slew rate control curve, or data representative thereof, are used to control an operation of an electric drive motor of the vehicle for the defined time period.