Predicting Future Time Intervals Using Dynamic Error Ratios
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for predicting time intervals in engine control systems are imprecise due to the neglect or simple summation of average errors, leading to inaccuracies in determining future time intervals, especially during acceleration or deceleration periods.
Innovation Solution
A method that calculates the predictive value of future time intervals by incorporating the average error multiplied by the ratio of past interval increments, allowing for more accurate predictions by using stored past values and accounting for periodic conditions and deviations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If existing prediction methods (simple summation of average errors) are used, then the calculation is simple, but the prediction accuracy deteriorates during acceleration or deceleration periods
Solution Approach 1:
The patent changes the prediction parameters by introducing the ratio of successive time intervals (DT(-k+1)/DT(-k)) as a dynamic correction factor. Instead of using a fixed average error summation, the method adapts the prediction by multiplying the average error by this ratio, allowing the prediction to automatically adjust to acceleration or deceleration conditions while maintaining computational efficiency.
2Productivity
If the average error is simply summed for prediction, then the computation is fast, but the prediction accuracy deteriorates under non-uniform rotational speeds
Solution Approach 1:
The patent introduces dynamics into the prediction method by using the ratio of successive time intervals (DT(-k+1)/DT(-k)) as a dynamic correction factor. This ratio automatically adapts to changing rotational speeds, making the prediction method responsive to acceleration and deceleration without requiring complex real-time calculations, thus maintaining computational speed while improving accuracy.
3Reliability
If markings are left out in the sensor wheel for synchronization, then the synchronization is achieved, but the angular basis becomes rough and requires prediction
Solution Approach 1:
The patent implements feedback by using the actual measured time interval DT(0) to correct the prediction. The average error is calculated based on the difference between predicted and actual values, and this error feedback is then used to improve future predictions through the corrected formula, creating a self-improving prediction system that compensates for the rough angular basis.
Data Source
AI summary
A method for predicting a value for a length of a future time interval in which a physical variable changes is described, in which at least one measured value for the length of a past time interval and an instantaneously measured value for a length of an instantaneous time interval are taken into account, m values for lengths of past time intervals being added. A first value precedes the instantaneously measured value by k−1, and an mth value precedes the instantaneously measured value by k−m. The m added values are divided by a value for a length of a past time interval which precedes the instantaneously measured value by k. A ratio of the mentioned values is formed. For determining the value to be predicted, an average error is initially added to the instantaneously measured value, forming a sum. The formed ratio is subsequently applied to this sum.