Study Will Analyze Maintenance Data From NGV Truck Fleets

December 1, 2020

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While heavy-duty natural gas vehicles (NGVs) have been making strides in the trucking industry for the past decade, technicians continue to face challenges when maintaining these alt-fuel engines. But with some experience and the right training, NGVs can also create success stories that echo their benefits.

NGV maintenance issues can sometimes result from improperly sized engines, insufficient or improper routine maintenance, or design problems with early generation natural gas engines. However, information remains anecdotal, and the lack of solid data and analyses can create confusion and uncertainty. These concerns can also lead to barriers to the adoption of more NGVs in the on-road sector.

NGV UP-Time will analyze maintenance data from NGV fleets to provide a clear understanding of costs and benefits.

Clean Fuels Ohio Leading NGV UP-Time Project

Clean Fuels Ohio is leading a team of researchers, industry experts, and Clean Cities coalitions to address these concerns and market barriers. NGV UP-Time, a project funded by the U.S. Department of Energy, will gather, distill, and analyze maintenance data from NGV and diesel over-the-road medium- and heavy-duty trucks specifically in freight and goods movement applications. The data will provide current and future NGV fleets, as well as industry suppliers, a clear understanding of NGV maintenance: factors that can lead to problems, strategies for success, and more accurate predictions of costs and benefits of switching to NGVs for over-the-road trucks.

Gathering data from trucking fleets is critical to the success of this project. Without it, we cannot effectively analyze and make clear and useful recommendations, which is why we are looking for cooperation and support from NGV industry partners and trucking fleets.

The specific data we require, both historic and recent, includes:

Fleet Vehicle & Maintenance Data Points
Vehicle Data Vehicle Year/Make/Model, Vehicle Type, Vehicle Application, Vehicle Number, Mileage when Service was Performed
Engine Data Year, Manufacturer, Year, Exhaust Aftertreatment Components (e.g., diesel particulate filter [DPF] and Selective Catalytic Reduction [SCR] system), Engine Hours when Service was Performed
Repair Data Repair Order Number, Open Date, Close Date, Root Cause of Service (e.g., Part Failure, Preventative Maintenance, or Accident)
Repair Costs Parts, Labor, Who Performed Service (e.g., In-House or Vendor) for each Work Order Component

Participating fleets will receive significant benefits for providing data to the project as well:

  • Individual Fleet Maintenance Data Analysis Report
    • Summary data report showcasing trends, findings, and graphical assessment of major parameters by vehicle powertrain, year and model, repair cost per mile, repair frequency, and vehicle utilization
    • Data to help fleets answer operational questions comparing natural gas and diesel vehicles and assess cost reduction strategies.
  • Secured Fleet Partnership Agreement
    • Data Provision Agreement guaranteeing the fleet receives data protection, anonymity, and a fleet specific analysis report and that the fleet will provide maintenance data to project team and U.S. DOE.
  • Full Report
    • Includes key recommendations on best practices and technology solutions to reduce NGV maintenance costs

We, along with our project partners, have launched NGV UP-Time because we want NGV trucking fleets to be successful and reap the environmental and economic benefits of natural gas. We want our industry partners to grow the market. To achieve these results, we need fleet data. Contributing fleets will gain specific benefits, and all of us will benefit from strong, successful growth in NGV use.

To learn more about NGV user experiences across the country, visit the Alternative Fuels Data Center website highlighting natural gas vehicle fleet case studies and success stories.

To provide fleet data or learn more, contact Tim Cho at or Andrew Conley at, or call (614) 884-7336. Learn more about the U.S. DOE funded project at