Adaptive Hybrid Vehicle Control System for Load-Based Energy Optimization
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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 usage based on detected load categories and usage factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
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 system dynamically adapts control parameters based on real-time load conditions. The controller monitors vehicle operation parameters (speed, acceleration, load) and adjusts control curves and slew rates accordingly, transforming a static control system into a dynamic one that optimizes fuel efficiency across varying operating conditions.
Solution Approach 2:
The system changes control parameters (current limits, slew rates) based on detected load categories. Different parameter sets are applied for different operating modes (light load, heavy load, transient conditions), allowing the control system to optimize performance and fuel consumption for each specific condition without requiring a completely different control architecture.
2Use of energy by moving object
If the hybrid vehicle relies 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 balance between electric drive and internal combustion engine based on real-time load conditions. Under heavy load conditions, the controller increases engine contribution while maintaining electric drive assistance, dynamically optimizing the power split to ensure adequate performance while managing fuel consumption.
Solution Approach 2:
The system modifies control parameters including current limits and slew rates based on load category detection. Under heavy load conditions, the controller adjusts parameters to allow greater engine power contribution while maintaining appropriate electric drive limits, ensuring vehicle performance requirements are met while optimizing fuel usage.
3Ease of operation
If the hybrid vehicle operates under light load conditions with standard control, then the system is simple to operate, but fuel efficiency deteriorates due to excessive engine fuel burn
Solution Approach 1:
The control system automatically detects load conditions and adjusts control parameters without requiring driver input or manual intervention. The classifier autonomously categorizes operating conditions (light load, heavy load, transient) and the controller self-adjusts control curves and slew rates accordingly, maintaining ease of operation while optimizing fuel efficiency.
Solution Approach 2:
The system changes control parameters based on detected load conditions. Under light load conditions, the controller adjusts current limits and slew rates to reduce engine fuel consumption while maintaining adequate vehicle performance, automatically optimizing energy usage without complicating the driving experience.
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.