The fuel savings must be calculated based on very long driving cycles, as variations in the way the car is driven and charged plays a major role in fuel consumption. Analysing the fuel efficiency of different plug-in hybrids over long cycles is time-consuming as a month of driving has to be analysed second by second.
Mitra Pourabdollah presents a quick and simple method to calculate the lowest cost, in her doctoral thesis. It factors in both manufacture and driving behaviour.
"The operating cost of a plug-in hybrid depends on many different variables, such as the way you drive, how you charge the battery and how far you drive between charges," she says. "Driving habits also affect what size battery you need. Component prices, different battery types and different driving habits combined result in a huge number of parameters that impact the overall cost."
Using a convex optimisation algorithm which acts as a tool, the researchers entered the various parameters that can affect the cost of a plug-in hybrid. The results are shown quickly – the method speeds up this part of the design process 20-fold. In extreme cases, calculations that would normally take a thousand hours can be completed in half an hour – almost two thousand times faster.
Pourabdollah's research colleagues Nikolce Murgovski and Lars Johannesson Mårdh originally came up with the idea of applying convex optimisation to a complex vehicle model. They began by developing a method for plug-in hybrid buses. Following on from their work, Pourabdollah studied how the method could be applied to passenger cars. The basic algorithm is very flexible.
"Finding a way to describe the various components that fit convex optimisation is a bit like a game," explains Pourabdollah. "The method has many other application areas as well, for example in active safety".
