Transportation Systems

Intelligent Transportation Systems (ITS) research focuses on new technologies that can improve vehicle systems, such as safety, energy management and traffic management. ITS innovations enable users to be better informed and make safer, ‘smarter’ use of vehicles and transportation networks.

James Wollaeger, a former Ohio State University graduate student in electrical and computer engineering, investigated the use of ITS theories and applications to improve energy management systems of plug-in hybrid electric vehicles (PHEVs). These vehicles are a particular challenge to control engineers, because they operate with two power sources – an internal combustion engine (ICE) and a battery-powered electric motor (EM).

Wollaeger centered his studies on a power-flow based model of Ohio State’s Challenge X vehicle and the dynamic equations that form the vehicle model. The vehicle was designed for a 2004 competition, where student teams converted small SUVs into hybrid electric vehicles. The simulator was modified from its original form to reflect a prototypical PHEV.

“We set the simulation resolution at 500 watts, which resulted in about 40,000 possible states-of-charge for each time step,” explained Vincenzo Marano, Ph.D., a senior research associate at OSU’s Center for Automotive research who assisted Wollaeger. “Because of the huge number of possible solutions – which required a large amount of memory and resulted in long runtimes – we leveraged Ohio Supercomputer Center resources to solve this optimization problem.”

Wollaeger implemented a control strategy, called the Adaptive Equivalent Consumption Minimization Strategy (A-ECMS), and compared its solution to the global optimal solution. Applying a dynamic programming algorithm to determine the optimal power split between the two power sources established the global optimal solution and produced a state-ofcharge profile that would consume the least fuel over the driving cycle. The usable energy in the battery is defined as between 95 percent and 25 percent, because of battery life concerns. Wollaeger’s studies yielded the first implementation studies of the Finite Horizon A-ECMS control strategy on a PHEV operating across varying road load conditions.

“We have shown that this control strategy is successful in minimizing the fuel consumption in PHEVs that have no velocity prediction error,” Wollaeger said. “In a world where more data is available every day, tomorrow’s vehicles should be designed to take advantage of that data to optimize fuel consumption by advanced energy management control systems.”


Project lead: Vincenzo Marano, The Ohio State University

Research title: ITS in energy management systems of PHEVs

Funding source: The Ohio State University

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