Expertise on hand

Since the introduction of the electronic diesel engine more than a decade ago, many new computing and wireless technologies have emerged to greatly simplify access and visibility to a range of vehicle operational data.

Accessing data today is not as challenging as in years past. The real challenge is using this data to sustain fuel efficiency and achieve incremental improvements. Increasingly, this challenge requires more skillful analysis.

Volvo Trucks of North America recently announced its Fuelwatch initiative to help customers achieve sustainable fuel efficiency. Among other things, the plan involves commercialization of a technology Volvo has used for many years to analyze the logged vehicle data (LVD) of its engines.

Starting with the introduction of the Volvo D12 engine in 1998, the company has captured a complete history of raw operating data from a large population of engines. Each time a technician connects a service tool to diagnose or reprogram an engine, the data is downloaded and backed up on a server, says Seth Gruber, director of business solutions for VTNA.

In 2001, Volvo created a central database for its LVD. Originally, the company used the database internally for high-level engineering purposes. In 2004, the database matured as Volvo used it to validate real-world performance of engines designed to meet the new emissions rule, says Peter Blonde, VTNA’s project manager of customer satisfaction.

Shortly thereafter, Volvo began to use its database and software tools for special customer projects. For example, Blonde once used LVD to resolve a customer complaint about the fuel economy of new vehicles. The fuel economy of four out of the 10 new trucks the customer purchased was “far off” relative to the other six. Blonde’s analysis showed that the fuel economy trends correlated to certain dates. He asked where the trucks were dispatched during the days in question.

“The (four) trucks were going to Pennsylvania and New York, while the rest of the trucks were going to Dallas,” he says. Blonde used LVD to explain the deviations of the four trucks by looking at the torque profiles between the two vehicle sets. “It is an error to lump all new trucks into one group and then look at mpg,” he says.

Typically, Blonde uses LVD to pinpoint areas where a customer’s operational data exceeds the parameters for optimal fuel economy, such as coolant temperatures or speed. “I look for exceptions,” he says. “That’s what the customer is interested in.”

Later this year, Volvo plans to offer its expertise of LVD analysis to customers as part of its Fuelwatch initiative, Gruber says. Through its dealer network, for example, the company can assign a trained analyst to work with a customer to create driver scorecards based on how they perform in different categories for fuel efficiency. The scorecards can show drivers how they rank relative to the fleet average and to the vehicle’s optimal parameters.

This scorecard approach, based on analysis of a fleet’s data, can be integrated directly into the dashboard to give the driver real-time feedback. Since 2006, Volvo has included a performance bonus guide in its electronic dash display. Icons appear in the display based on how the driver operates the vehicle for maximum fuel efficiency. Goals can be set for categories that include engine load, speed, RPM, idle time and fuel economy. A fleet can set these goals according to the specifics of their operations; for example, a group of drivers that run heavier loads or higher grades may have a lower threshold for mpg.

Ultimately, Volvo will be able to show fleets how any number of variables compare to a mass LVD population from similarly spec’d Volvo trucks, Gruber says.

Volvo’s Fuelwatch initiative demonstrates how a truck manufacturer can leverage its expertise in data analysis to develop a new commercial offering for its customers – one that can save them critical dollars at the pump.