Hybrid Powertrain Control for Battery Health and Torque Distribution
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Solution Overview
Problem
Current powertrain systems face challenges in efficiently managing electric power and torque distribution across hybrid powertrains, particularly in optimizing engine and electric machine interactions to enhance fuel economy, emissions, and drivability while maintaining battery health.
Innovation Solution
A hybrid powertrain system with a two-mode, compound-split, electro-mechanical transmission and energy storage device, controlled by a distributed control module system that coordinates engine, electric machine, and transmission operations to optimize torque distribution, energy efficiency, and battery charging based on predictive power limits and operator inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If the energy storage device operates without predictive power limits, then immediate power availability is maximized, but long-term battery health and durability deteriorate
Solution Approach 1:
The control system performs preliminary actions by establishing predictive short-term and long-term power limits before the battery reaches damaging operating conditions. These predictive limits are calculated based on battery state-of-charge, temperature, and aging characteristics, preventing the battery from entering harmful operating zones while still allowing maximum safe power delivery.
Solution Approach 2:
The power limits are made dynamic rather than static, adjusting in real-time based on battery state-of-charge, temperature, and predicted future operating conditions. This allows the system to maximize immediate power availability when conditions permit while automatically reducing limits when battery health concerns arise, creating a adaptive balance between power and durability.
2Productivity
If the powertrain system uses complex predictive algorithms for power management, then fuel economy and emissions are optimized, but system complexity and computational requirements increase
Solution Approach 1:
The complex power management problem is segmented into separate functional modules: predictive power limit calculation, torque distribution optimization, and real-time control execution. Each module handles a specific aspect of the optimization, making the overall system more manageable and implementable while still achieving fuel economy improvements through coordinated operation of all modules.
3Device complexity
If the transmission operates in fixed gear ranges, then mechanical simplicity is maintained, but adaptability to varying power demands decreases
Solution Approach 1:
The transmission system incorporates dynamic gear range selection that adapts to varying power demands through electronic control. The system can smoothly transition between different gear ranges based on real-time operating conditions, power requests, and efficiency optimization goals, providing versatility while maintaining relatively simple mechanical architecture through intelligent control.
Data Source
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AI summary
A method for controlling a powertrain system includes monitoring a state-of-charge of the energy storage device (74) and determining a first set of electric power limits and a second set of electric power limits based on the state-of-charge of the energy storage device (74). The method further includes providing a power range for opportunity charging and discharging of the energy storage device (74) based on the first set of electric power limits. The method further includes providing a power range for controlling output power of the energy storage device (74) based on the second set of electric power limits.