IoT-Based Vehicle Research Tool Paves the Way to Autonomous Driving

This IoT-based tool lets fleet managers, engineers, and researchers access real-time data on vehicle use and performance.

Most people probably didn’t think about the intricate details of vehicle fleet optimization until a few years ago when the UPS “no left turn” guideline became public knowledge, but fleet managers are always looking for ways to decrease fuel consumption, shorten delivery times, and avoid accidents. As fleets move away from internal combustion engines (ICEs) in favor of hybrid and electric vehicles (EVs), EV research opportunities are becoming abundant. FleetCarma offers a real-time data logger and cloud-based tools that help fleet managers, engineers, and researchers collect, analyze, and use that information, helping to make the transition from ICEs to EVs and eventually, autonomous vehicles

The C2 Data Collection Device

FleetCarma’s C2 data logger plugs into a vehicle’s diagnostic port and collects a wealth of real-time information, including EV battery charge/discharge rates, state of charge, vehicle speed, throttle position, engine torque, ICE fuel consumption rates, engine RPM, temperature, and more. Its built-in cellular technology transmits the information to a secure cloud-based server, where fleet managers can access a dashboard to monitor data in a graphical format. Engineers and researchers may prefer raw data collected over time and tailored to their individual needs; in that case, FleetCarma provides consulting services to perform data analysis and prepare custom reports.

How a Fleet Manager Might Use the Data

Suppose a company has a fleet of ICE vehicles and wants to determine the feasibility of replacing them with plug-in hybrid electric vehicles (PHEVs) or battery electric vehicles (BEVs). The fleet manager would install a plug-and-play C2 data logger into each ICE vehicle and let it go about its business. During its travels, the C2 collects data and uploads it to the cloud. At the end of the data collection period, FleetCarma’s computer models predict how well a BEV or PHEV would perform under the same driving conditions. The models will actually do the comparison over multiple PHEVs and BEVs to see which vehicles hit the “sweet spot” of minimizing fossil fuel consumption while still having enough “juice” to complete the rounds. The software then finds which EV matches the user profile, balancing environmental benefits of EVs with vehicle total cost of ownership, and displays a side-by-side comparison of the current ICE vehicle with best-fit BEV/PHEV.

Research conducted with the C2 in British Columbia examined nine fleets with 123 vehicles and found that 94% of the routes could be handled by BEVs, which would result in a savings of $1.4M in fuel, $77k in maintenance, and $87k in emission costs over a seven year vehicle lifespan. (Emission costs are based on British Columbia’s carbon tax.)

EV Impact on Utilities

Converting a fleet to EVs also presents a challenge to utilities by increasing the load and demand on the power grid. A pilot study in Toronto, Ontario used FleetCarma’s tools to monitor thirty participating EVs and determined that “paired smart charging,” where the utility can throttle back EV charging depending on demand and user preferences, allowed utilities to shift 85% of the peak load to off-peak hours. At the end of the year-long study, 97% of the EV owners reported no negative impacts on their EV charging.

Unlike a utility controlling consumers’ air conditioners to prevent summer brownouts, the EV charge manipulation offers year-round benefits. Consumer participation, of course, is optional, and participating EV owners can set daily parameters to guarantee that their vehicles will be fully charged when needed and that their batteries’ state of charge will never dip below a certain level under any circumstances.

A Bright Idea: Solar Charging

Alameda County (California) has hundreds of ICE vehicles in its municipal fleet. County officials want to convert the fleet to EVs, but doing so would subject the county to an additional $60k in annual tariffs imposed on customers who use large amounts of electricity. Moreover, the facility would need over $100k in upgrades to its electrical infrastructure. It seems like a no-win scenario, until you shed a little light on the situation – sunlight, that is. The county is currently investigating the use of stand-alone solar charging stations with built-in Li-ion battery packs to enable the fleet to charge at any time of the day or night. Charging stations that are near utility lines may even be grid-tied, allowing the county to sell excess solar electricity to the utility when it’s available. The optimal size of a charger’s battery bank will depend on the vehicles that it services, and that’s where data collection and analysis tools come into play. By analyzing the paths of existing ICE vehicles and selecting the best EV for the job, a fleet manager can then choose chargers and battery banks that will keep the vehicles rolling throughout their routes.

The Road to Autonomy

Obviously, autonomous vehicle control systems need to monitor vehicle behavior and traffic patterns, but it would also help to know what other vehicles are doing. Just as “regular” cars have turn signals and brake lights to inform other drivers of their intentions, AVs will feature vehicle-to-vehicle communication systems. (Unlike many of our fellow commuters, AVs won’t forget to signal.) These monitoring and reporting devices will provide data to other AVs and deliver real-time traffic reports – no “traffic-copter” required!

Converting to EVs and AVs will require big data coupled with heavy-duty analysis. I suspect that we’ll see more real-time data collection, reporting, and analysis tools as the industry matures. It’s an exciting time to be an engineer in the auto industry!

Images courtesy of FleetCarma


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