Dynamic Transmission Shift Schedule Adjustment
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Solution Overview
Problem
Conventional transmission systems in vehicles do not effectively optimize vehicle operating parameters such as fuel economy and acceleration characteristics across different vehicle types, as they rely solely on engine load and speed, failing to account for unique vehicle losses like aerodynamic and rolling resistance, leading to suboptimal performance and operator behavior changes.
Innovation Solution
A controller integrated with the vehicle's powertrain system dynamically adjusts the transmission shift schedule based on real-time data, including vehicle losses and acceleration requirements, to optimize parameters like fuel consumption, emissions, noise, and acceleration, by adjusting shift points and schedules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional transmission systems rely solely on engine load and speed for shift scheduling, then the system structure remains simple, but fuel economy and acceleration performance are suboptimal due to failure to account for vehicle-specific losses
Solution Approach 1:
The transmission shift schedule is dynamically adjusted based on real-time vehicle operating conditions, vehicle type characteristics, and calculated vehicle losses. The controller continuously modifies shift points and schedules to optimize fuel economy and acceleration performance for each specific vehicle configuration, transitioning from static to adaptive control.
Solution Approach 2:
The system changes key control parameters including shift schedule timing, shift points, and transmission settings based on vehicle type data and calculated vehicle losses. By modifying these parameters according to specific vehicle characteristics, the system achieves optimal fuel economy and acceleration without requiring hardware changes.
2Adaptability or versatility
If the transmission uses fixed shift schedules, then the control system remains simple, but acceleration characteristics and fuel efficiency cannot be optimized across different vehicle types
Solution Approach 1:
The system receives and stores vehicle type data in advance, including vehicle mass, aerodynamic characteristics, and other loss parameters. This preliminary data acquisition enables the controller to pre-calculate optimal shift schedules tailored to each vehicle type before actual operation begins.
Solution Approach 2:
The controller continuously monitors actual vehicle operating conditions and compares them with expected performance based on vehicle type data. This feedback mechanism allows the system to refine shift schedule adjustments in real-time, improving adaptability across different vehicle configurations and operating scenarios.
3Loss of energy
If shift schedules are optimized for fuel economy, then fuel consumption decreases, but acceleration performance may be compromised
Solution Approach 1:
The controller applies partial optimization by adjusting shift schedules selectively based on operating conditions. During acceleration-critical scenarios, the system maintains more aggressive shift timing to preserve acceleration performance, while during steady-state cruising, it implements later shift points to maximize fuel economy. This partial application of optimization strategies balances both objectives.
Data Source
AI summary
A method for a vehicle includes receiving a shift schedule for a transmission of a vehicle, the shift schedule indicating when shift events occur based on operation of the vehicle. The method further includes receiving vehicle operation data during operation of the vehicle. The method further includes determining a power to overcome vehicle losses based on the vehicle operation data. The method further includes determining an adjustment to the shift schedule to optimize a vehicle operating parameter based on the determined power to overcome vehicle losses and implementing the adjustment to the shift schedule.