Electric Machine Speed Sensor Selection for Common Axle Control
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Solution Overview
Problem
In electric vehicles with multiple electric machines powering a common axle, accurately selecting a representative speed signal for control is challenging due to variations in speed measurements, which can lead to inefficiencies in speed control and regenerative braking.
Innovation Solution
A controller is programmed to select the speed sensor with the greatest number of accumulated points based on variance and noise factors, using a weighted summation of points over a sampling duration, to determine the representative motor speed signal, and then commands speeds to the electric machines based on this selected signal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple speed sensors are used to measure electric machine speed, then measurement reliability can be improved through redundancy, but measurement precision deteriorates due to variations and noise in the speed measurements
Solution Approach 1:
The system performs preliminary evaluation of multiple speed sensor signals before control execution. The controller calculates variance and noise factors for each sensor signal in advance, accumulates points based on these metrics, and selects the best sensor beforehand. This preliminary selection process ensures that the most reliable signal is chosen for control, resolving the contradiction by preparing the optimal measurement in advance rather than using all signals equally or selecting during control execution.
Solution Approach 2:
The system implements feedback by continuously monitoring the performance of each speed sensor through variance calculation and noise factor analysis. The controller uses accumulated points from multiple sampling periods to dynamically select the best sensor signal. This feedback mechanism allows the system to adapt to changing conditions and maintain both reliability through redundancy and precision through selective usage of the best signal.
2Measurement precision
If a single speed sensor signal is selected for control, then measurement precision is improved, but reliability deteriorates due to lack of redundancy
Solution Approach 1:
The controller performs preliminary evaluation of all available speed sensor signals by calculating variance and noise factors before selecting the best one for control. This advance assessment ensures that the selected single signal is the most precise while the evaluation process itself maintains reliability through comprehensive assessment of all redundant signals.
Solution Approach 2:
The system changes the parameter being controlled from using multiple signals simultaneously to selecting a single best signal based on evaluated parameters (variance and noise factors). By evaluating multiple signals and selecting the one with optimal characteristics, the system achieves both precision (using the best signal) and reliability (through evaluation of all signals).
3Reliability
If all speed sensor signals are used for control, then reliability is improved through redundancy, but device complexity increases due to multiple signal processing requirements
Solution Approach 1:
The system extracts only the essential evaluation metrics (variance and noise factors) from multiple speed sensor signals and uses these to select a single representative signal for control. Instead of processing all signals equally through the control algorithm, the system extracts the best signal based on predefined criteria, reducing processing complexity while maintaining reliability through the extraction and selection process.
Solution Approach 2:
The system implements self-service by automatically evaluating and selecting the best speed sensor signal without external intervention. The controller autonomously calculates variance, determines noise factors, accumulates points, and selects the optimal signal for control. This self-service mechanism reduces the complexity of manual signal selection while maintaining high reliability through consistent automated evaluation of all redundant signals.
4Measurement precision
If variance and noise factors are calculated for sensor selection, then measurement precision is improved, but loss of time increases due to additional processing during sampling
Solution Approach 1:
The system performs variance calculation and noise factor analysis as preliminary actions during the sampling period before control execution. By completing these calculations in advance and accumulating points over multiple sampling periods, the system prepares the selection criteria beforehand, reducing the time required during actual control operations while maintaining precise sensor selection.
Data Source
AI summary
A vehicle includes first and second electric machines constrained to rotate in unison and configured to power a common axle. A controller is programmed to, in response to activation of the vehicle, select one of the first and second speed sensors as a representative speed sensor, and, in response to the electric machines being in speed control, command speeds to the first and second electric machines based on a difference between a target speed of the electric machines and a measured speed of the representative speed sensor.