Engine Oil Remaining Life Estimation from Telematics Data
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Solution Overview
Problem
Existing vehicle engine oil quality estimation systems, reliant on proprietary algorithms, often fail to accurately predict the remaining useful life of engine oil due to changes in operational factors, leading to premature or late oil changes, resulting in wasted resources and increased maintenance costs, especially in fleet management.
Innovation Solution
A system that utilizes telematics data from multiple vehicles to determine the start point of an oil cycle by identifying significant changes in engine oil quality, synchronizes odometer and engine oil quality data, and applies a regression model to estimate the remaining useful life of engine oil based on current operational factors, independent of previous cycles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If proprietary algorithms based on expected operational factors are used to estimate engine oil quality, then the system can provide oil quality estimation, but the accuracy deteriorates when actual operational factors differ from expected factors
Solution Approach 1:
The system dynamically changes the parameters used for oil quality estimation from static expected factors to actual measured operational factors. By continuously monitoring real-time data such as actual driving conditions, vehicle load, temperature, and humidity, the system adjusts its estimation parameters to match current operational reality, thereby maintaining accuracy across varying conditions
Solution Approach 2:
The system uses the vehicle's own operational data to estimate its own oil quality without relying on pre-programmed expected factors. The vehicle effectively serves itself by providing the actual operational context needed for accurate estimation, eliminating the mismatch between expected and actual conditions that plagues proprietary algorithms
2Productivity
If oil changes are performed based on inaccurate estimates, then maintenance can be scheduled, but resources are wasted through premature changes or engine damage occurs from late changes
Solution Approach 1:
The system implements continuous feedback by monitoring actual operational factors and adjusting oil quality estimates in real-time. This feedback loop ensures that maintenance scheduling is based on actual oil degradation patterns rather than static schedules, preventing both premature oil changes (wasting oil) and late changes (risking engine damage)
3Device complexity
If proprietary algorithms with fixed operational factors are used, then the system complexity remains low, but the reliability of oil quality estimation deteriorates under varying conditions
Solution Approach 1:
The system transitions from static fixed factors to dynamic actual measured factors. By continuously updating operational parameters based on real-time sensor data, the system maintains reliability under varying conditions without requiring complex proprietary algorithms, achieving adaptability through dynamic data collection and processing
Data Source
AI summary
Disclosed herein are systems and methods for estimating remaining useful life of vehicle engine oil. Such methods may comprise operating at least one processor to: receive telematics data originating from a plurality of vehicles, the telematics data comprising odometer data and engine oil quality data associated with each of the plurality of vehicles; determine, for one or more of the plurality of vehicles, a start point of a current oil cycle based on when an oil cycle event previously occurred by identifying within the engine oil quality data: a first series of engine oil quality datapoints, and a second series of engine oil quality datapoints immediately following the first series, a difference between a final datapoint of the first series and an initial datapoint of the second series being greater than a predetermined threshold; synchronize the odometer data and the engine oil quality data by associating odometer datapoints and engine oil quality datapoints reported within a same time period; determine a remaining useful vehicle engine oil distance by applying to synchronized odometer and engine oil quality data reported during the current oil cycle a regression model; and determine a remaining useful vehicle engine oil time by converting the remaining useful vehicle engine oil distance thereto based on an average difference in odometer datapoints reported during a selected time period, whereby the remaining useful life of vehicle engine oil is estimated based on vehicle operational factors associated with the current oil cycle, and independently from those of a previous oil cycle.