A Data Driven Approach To Enhancing Gear Shifting Efficiency

At Intangles our core objective is to drive the most ‘potent’ KDD(knowledge derivation from data) cycles on telemetry data. Our analytics platform ‘Indium’ has been threaded to mine ‘mission—critical’ data points from complex telemetry data which are conveniently consumed by the every day fleet manager.

Intangles recently created a very powerful case study for one of the largest fleet operators based out of Pune. When Intangles approached the Maintenance team, it was presented with multiple challenges they were facing in vehicle upkeep and performance optimization. One of the major issues was gear utilization efficiency. The problem statement was that most of the drivers were using second gear to initiate motion from a standstill. This had a far reaching impact on vehicle performance and upkeep. Firstly the mileage would take a significant hit as starting in higher gears would require more fuel to draw the same power from the engine than starting in first gear.

The above does not go without stating that the subject here is a 5700 cc powerful and extremely fuel thirsty natural gas engine, shelling out 125 bhp and 416 nm of torque at peak performance. Second, in most cases, the first gear train mostly remained unused as a resultant of the driver behavior. Third, such driving characteristics aggravate clutch deterioration.

Intangles through its proprietary algorithm studied the driver behavior pattern and found out that the ground reality was much worse than the premonitions of the maintenance team. The statistical distribution of gears employed during pick up from standstill is shown in the figure below.

Before moving forward with the comparison following prerequisites were set

  1. The vehicles being evaluated here are of same make and model
  2. Are used under same traffic and ambient conditions.
  3. High frequency data capture by OBD instrumentation(‘Ingenious’) to provide largest possible sample set
  4. Both the vehicles have same Fuel Rate under peak torque conditions. This was done to ensure that their Vehicle Health Profiles are comparable and we do Apple to Apple comparison

For the first vehicle, the driver was being trained based on consultation and feedback for better driving behavior with Gear Shifting as one of the major aspects. The second driver was kept uninformed.The data from the vehicle was monitored over a period of 1 month. The mileage difference between the two vehicles showed the power of data in managing not only machines but human behavior and bringing the best out of it.

The mileage of the first vehicle (C-110) was 2.95 KM/KG and the second (C-139) was 2.41 KM/KG. This converted into a loss of Rs 3.34 per KM. In the bigger scheme of things this converts to a significant loss considering these buses cover over 200 km per day. The annual losses in such cases are around Rs.2 Lakhs on the badly driven vehicle.

With proper feedback and data exploration, Intangles not only allowed the customer to identify the problem, its magnitude and repercussions but also helped him take an’ informed decision and design an ‘effective’ strategy for ‘improvement’ rather than creating a company-wide memo which nobody reads or conveniently forgets to remember.

About Ingenious

“InGenious” is a first of its kind, made in India Intelligent Vehicle Health Monitoring system which helps Fleet Owners increase revenues – by increasing up time/operational hours of their vehicles and improve profitability – by reducing maintenance cost, fuel pilferage’s etc. The Management System helps fleet owners/decision make informed decisions through Centralized predictive actions to increase operational efficiency by real-time monitoring of their assets(vehicles) – a Single platform for maintenance and tracking of the assets.“InGenious” provides the following features in real time basis:

  • Predictive Vehicle Health Monitoring
  • Bench-marking of performance of Vehicles
  • Driving Behavior
  • Operational Automation
  • Location Tracking
  • Alerts and Notifications

Leave a Reply

Your email address will not be published. Required fields are marked *