Every electric vehicle driver is familiar with the “riddle-o-meter,” the dashboard display that estimates a vehicle’s remaining range. A team of Japanese researchers claims to have found a way to make EV range estimates more accurate. Furthermore, they point out that inaccurate range estimates lead to inefficiency and waste.
The flagship MEXT Q-LEAP project, led by researchers from the Tokyo Institute of Technology and Yazaki Corporation, has developed a prototype diamond quantum sensor capable of measuring currents over a wide range with milliampere precision. The researchers say their technology can improve detection accuracy from 10% to around 1%.
The state of charge (SoC) of an EV battery is measured based on the current output of the battery, and this measurement is used to estimate the remaining range of the vehicle. According to Tokyo Tech’s Professor Mutsuko Hatano, battery currents in electric vehicles can reach hundreds of amperes, but commercial sensors capable of detecting such currents cannot measure small milliampere-level changes. This leads to an ambiguity of around 10% in the battery charge estimate.
In a study published in Scientific reports, Hatano and his team describe a detection technique based on a quantum diamond sensor that can estimate the state of charge of a battery with an accuracy of 1%. “We have developed diamond sensors sensitive to milliampere currents, and [are] compact enough to be implemented in automobiles. In addition, we measured currents in a wide range [and] detected milliampere-level currents in a noisy environment,” says Professor Hatano.
Measuring the SoC more accurately could offer more than just convenience to drivers – the Tokyo team says their technology could help extend an electric vehicle’s range by 10% and increase efficiency battery usage. The implications could be profound. “Increasing battery utilization efficiency by 10% would reduce battery weight by 10%, which would reduce operating energy by 3.5% and production energy by 5% by 20 million new electric vehicles in 2030,” says Professor Hatano.
Source: Tokyo Tech News