A friend of mine has recently left telecom to work at MIT’s Lincoln Labs on the Smart Grid. He like many of our friends is a graduate of that technical training school (as Harvard refers to MIT). He pointed out some interesting facts over the weekend when we talked, but clearly much of the work is still in the experimentation stage and not ready for prime time.
One article on the Lincoln Labs website that caught my eye was about the optimization of hybrid electric vehicle routes. It caught my eye because it brought a new element to the choice of the commuting path. For many of us, the commute puts us on highways that get clogged and congested and the optimization of the Interstate is lost during the commute to and from work.
Enter the work at Lincoln Labs to optimize the battery use in an electric vehicle, and now the decision of “what route” is no longer “which route gets me there faster,” but instead “what route saves me more money (buy side decisions).” The GPS in this case would have “a predictive control system which would gather route and elevation data from [the] global positioning system (GPS) navigation system in the vehicle, along with data already available in the car's computer systems, and learn about a driver's trips and driving habits. Drivers could either tell the system where they were headed or the system could figure that out on the basis of experience.”
In the example Nicolas Judson, Bill Millner and Bill Ross talk about on the site, Nicolas’ commute has a Boolean choice between Route 128 and Massachusetts Avenue. Their work with the electric vehicle seems counter intuitive to most with the thought that a route with a lot of traffic lights can actually be the better route for efficiency. Judson’s use of Massachusetts Avenue takes ten minutes longer but saves 20 percent of the vehicle’s fuel consumption not to mention that the choice of route does not only impact the commute but the rest of your ride since “By timing the trip so the battery reaches its minimum charge just as the driver reaches his destination, they predict they can get a 7 to 10 percent boost in engine efficiency, raising mileage to roughly 71 miles per gallon from the 66 mpg expected from certain plug-in hybrid electric vehicles.”
Accepting this data and displaying for a driver to make the right choice is going to require a value proposition.
I can see this being a difficult change in behavior for most of us. Somewhere in the heart of us there is a Demolition Man John Spartan (Sylvester Stallone) yelling “Override” and wanting to take control of the vehicle.
The GPS is going to have to not only provide me a choice of routes but a substantive dollar amount. Something like “This route will save you a tank of gas this month.” However, the derivative of submitting to the GPS analysis is also the ability of the battery being available for longer distances and using more of its charge and holding less in reserve.
The good news is the change in behavior has a buy side rationale. The bad news is we’ve got to get to work.
If it's 8:30 a.m. on a weekday, the GPS would know the driver is probably headed to work, for instance. Knowing when the demands for high torque would come, it could use the battery as much as possible and level the load on the gasoline engine over the entire trip, thereby operating the engine at optimal efficiency. And instead of using pre-set parameters, such as battery charge levels, to switch to gasoline, the system could make decisions on the basis of the trip. For instance, if the battery was getting low but the car was two minutes from home and had a little battery energy left, it could decide not to use the gasoline engine.
The Laboratory's research program includes not only the predictive control but also an effort to optimize the batteries and bring their costs down. Millner says that plug-in vehicle batteries should not only draw from the electrical grid but also feed power back into the grid, thus smoothing out power demands for buildings and reducing costs, making the whole plug-in vehicle infrastructure more economical. For example, if the car "sensed" that it had more than enough reserve battery power to get itself back home (where it could recharge during off-peak hours of electrical consumption), it could feed some of that power into the grid.The team has built a vehicle energy lab in the basement at Lincoln Laboratory and is awaiting a test vehicle they can use to gather more real-world data. They spent last year on analysis and modeling, and hope to build a working system in 2011.
Carl Ford is a partner at Crossfire Media.Edited by
Stefanie Mosca
