Vehicle Change-Data Spectral Processing for Compact Real-Time Control
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Solution Overview
Problem
Existing methods for processing vehicle data are inefficient in converting extensive change data into a compact form, particularly for dynamically varying variables, which hinders real-time vehicle functionality control and data transmission.
Innovation Solution
The method involves determining a spectral distribution of vehicle variables through Fourier analysis, such as FFT or MDCT, to convert dynamic and continuous change data into a compact form, enabling efficient transmission and real-time vehicle functionality control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If extensive change data is processed and transmitted directly, then data completeness is maintained, but data transmission efficiency and processing speed deteriorate
Solution Approach 1:
The patent applies parameter changes by transforming the data representation from the time domain to the frequency domain through Fourier analysis. This changes the parameters of the data (from time-series values to spectral components), enabling compact representation while preserving essential information characteristics.
Solution Approach 2:
The patent extracts only the most relevant information from the extensive change data by identifying and retaining only those spectral components that are necessary for accurate vehicle state representation. This extraction process removes redundant data while maintaining data completeness for control purposes.
2Measurement precision
If continuous monitoring of dynamic variables is performed, then measurement precision is improved, but data processing complexity and transmission requirements worsen
Solution Approach 1:
The patent transforms continuous variable data into spectral representations that capture the essential dynamics with reduced complexity. The Fourier transform converts complex time-domain signals into frequency-domain components that are easier to process and transmit while maintaining measurement precision.
Solution Approach 2:
The patent segments the continuous data stream into discrete spectral components through Fourier analysis. This segmentation allows the system to process and transmit only the essential frequency components rather than every continuous data point, reducing processing complexity while maintaining precision.
3Speed
If real-time vehicle control is implemented, then response time is improved, but data processing requirements and computational load worsen
Solution Approach 1:
The patent performs preliminary spectral analysis and data compression before the control action is needed. By pre-processing the data into compact spectral representations, the system reduces the computational burden during real-time control execution, enabling faster response without excessive computational power requirements.
Solution Approach 2:
The patent changes the data parameters from raw time-series measurements to compressed spectral representations. This parameter transformation reduces the amount of data that needs to be processed in real-time, lowering computational power requirements while maintaining the speed of control response.
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 the efficient processing, transmission, and utilization of vehicle data in a compact form, facilitating real-time vehicle control and data aggregation for improved vehicle functions.
Implementation Method 1
The spectral distribution is determined, in particular, by means of a time-discrete Fourier analysis, in particular by means of a Fourier transformation
Data Source
AI summary
The invention relates to processing data in connection with a vehicle. The processing includes determining change data characterizing a change in one or more variables in the vehicle. The processing further includes determining a spectral distribution, in particular a spectral distribution function, on the basis of the sensed or acquired change data of the one or more variables in the vehicle. The processing further includes providing the data on the basis of the determined spectral distribution for use outside the vehicle.