Powertrain Management via Predictive Tyre Rolling Resistance
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Solution Overview
Problem
Current motor vehicle powertrain management systems lack the ability to predictively optimize energy consumption due to the absence of real-time data on tyre rolling resistance coefficients, leading to inefficient energy use and reduced autonomy in electric and hybrid vehicles.
Innovation Solution
A method that determines a predictive rolling resistance coefficient for vehicle tyres based on factors like pressure, temperature, loading, and rotational speed, and uses this data to adapt powertrain operations, such as gear changes and energy source utilization, to optimize energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If real-time tyre rolling resistance coefficient data is not available, then powertrain management systems cannot predictively optimize energy consumption, but adding such measurement and prediction capabilities increases device complexity
Solution Approach 1:
The system performs preliminary determination of the rolling resistance coefficient using predictive models that incorporate tyre temperature, pressure, loading, and rotational speed data. By calculating the coefficient in advance rather than measuring it in real-time, the system enables predictive optimization of energy consumption without requiring complex real-time measurement infrastructure.
Solution Approach 2:
The patent introduces an intermediary predictive model that acts as a mediator between available tyre parameter sensors and powertrain optimization goals. This model translates readily measurable parameters (temperature, pressure, loading, rotational speed) into the rolling resistance coefficient, avoiding the need for direct complex measurements while enabling energy optimization.
2Ease of operation
If predictive rolling resistance coefficient determination is implemented, then finer powertrain control is achieved, but measurement and calculation precision requirements increase
Solution Approach 1:
The system determines the rolling resistance coefficient by monitoring changes in tyre parameters (temperature, pressure, loading, rotational speed) rather than requiring direct high-precision measurement of the coefficient itself. The predictive model processes these parameter variations to calculate the coefficient, reducing measurement precision requirements while maintaining control precision.
Solution Approach 2:
The implementation incorporates feedback mechanisms where the determined rolling resistance coefficient is fed back into the powertrain management system to continuously optimize control decisions. This feedback loop allows the system to adapt to changing tyre conditions and maintain precise control without requiring ultra-high precision measurements at all times.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for finer control of the powertrain, optimizing energy use, determining the best energy source to employ, and providing users with better estimates of vehicle autonomy by leveraging the future evolution of the rolling resistance coefficient.
Implementation Method 1
The tyre (10) generates internal heat by virtue of its operation
Implementation Method 2
The tyre (10) generates internal heat by virtue of its operation
Implementation Method 3
the rolling resistance coefficient of which varies as a function of the temperature, the pressure, the loading and the rotational speed of the tyre
Data Source
AI summary
A method for managing a powertrain (3) of a motor vehicle (1) comprises the following steps: (a) determining a predictive rolling resistance coefficient (Crr) for at least one tyre (10) of the motor vehicle (1); and (b) adapting the operation of the powertrain (3) according to the predictive rolling resistance coefficient (Crr) in order notably to optimize the energy consumption of the motor vehicle (1).