Dynamic Gear Ratio Selection Using Real-Time Efficiency Maps
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Solution Overview
Problem
Conventional vehicular gear selection systems lack dynamic information exchange between the engine and transmission, relying on static shift calibrations that do not utilize efficiency map information for optimal gear or gear ratio selection during operation.
Innovation Solution
A method is introduced to dynamically generate adjustment information based on engine, transmission, and vehicle operating conditions, including desired gear selection, engine fuel economy, and energy efficiency maps, to adjust shifting schedules and select or maintain an efficient gear ratio, using a system with a transmission and drive system component controllers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static shift calibrations are used with fixed algorithms, then device complexity is reduced and ease of operation is improved, but fuel efficiency and power output are compromised due to lack of dynamic adaptation
Solution Approach 1:
The patent implements dynamic shifting schedules that continuously adapt gear selection based on real-time engine operating conditions, efficiency maps, and power demands. The system transitions from static pre-programmed calibrations to dynamic real-time optimization, allowing the transmission to respond adaptively to changing operational requirements while maintaining system manageability through structured control algorithms
Solution Approach 2:
The system incorporates feedback mechanisms by continuously monitoring engine operating parameters, efficiency map data, and power requirements. This feedback loop enables the controller to dynamically adjust shifting schedules and gear selection decisions, optimizing fuel efficiency and power output based on actual operating conditions rather than relying solely on pre-determined static calibrations
2Productivity
If static shift calibrations determined in offline process are used, then manufacturing precision and reliability are improved, but fuel economy and efficiency are worsened due to inability to utilize real-time efficiency map information
Solution Approach 1:
The patent performs preliminary actions by pre-calculating and storing efficiency maps and shifting schedules for various operating conditions during the manufacturing process. These pre-computed data structures enable rapid real-time decision-making without requiring complex on-the-fly calculations, thus improving fuel efficiency while maintaining computational feasibility and system reliability
Solution Approach 2:
The system dynamically changes operational parameters by adjusting gear selection and shifting schedules based on real-time engine operating conditions and efficiency map data. The controller modifies shifting behavior according to varying parameters such as engine speed, load, temperature, and efficiency characteristics, enabling optimized fuel economy across different operating regimes rather than using fixed calibration parameters
3Loss of energy
If dynamic adjustment of shifting schedules based on efficiency maps is implemented, then fuel economy and power output are improved, but device complexity and information processing requirements increase
Solution Approach 1:
The patent segments the efficiency maps and operating conditions into discrete regions and predefined shifting schedules. By dividing the continuous operating space into manageable segments with optimized shift points, the system achieves dynamic fuel efficiency optimization without requiring overly complex continuous optimization algorithms, thus balancing performance improvement with computational tractability
Solution Approach 2:
The system optimizes energy efficiency by dynamically changing gear selection and shifting parameters based on real-time operating conditions and efficiency map data. The controller adjusts shifting schedules to maintain operation within high-efficiency regions of the efficiency maps, reducing fuel consumption while managing system complexity through structured parameter adjustment rather than uncontrolled optimization
Data Source
AI summary
A method in a system having a transmission and a drive system component is disclosed. The transmission includes two or more gears defining one or more gear ratios and a gear-selection controller having shifting schedules and the drive system component includes a drive system component controller. The method comprises dynamically generating adjustment information having information selected from the group consisting of (i) a desired gear selection; (ii) a desired drive system component speed operating point (iii) engine fuel economy improvement information related to a selection of a desired gear of the two or more gears; (iv) a drive system component energy efficiency map, and (v) a combination thereof, and wherein the generated information relates to one or more given drive system component power levels and adjusting the shifting schedules using the adjustment information.