Spark EV Technology today announced a successful collaboration with BP that provided real-world trials which validated its advanced range prediction system for electric vehicles (EVs).
Range and time anxiety are key factors holding back drivers and businesses from buying EVs. By delivering more accurate range predictions, based on actual driving style, topography and current atmospheric conditions, Spark’s proprietary technology overcomes these fears and increases driver trust that they will be able to get to their destination without needing to recharge. As Spark’s AI algorithms learn with every journey, it continually improves the accuracy of personalised journey predictions.
The project saw BP employees based at five locations drive 10,000 km in two types of EVs equipped with Spark’s journey prediction solution and supplied by Zipcar and Avis Budget Group. As part of the testing phase, drivers entered their proposed journey into Spark’s smartphone application to record data and make comparisons with the onboard range display. They then received personalised advice on whether they could complete it – based on live data, driving style, urban/country routes, previous trips and charge point locations.
When it comes to EVs, incorrect range predictions impact drivers in two ways. Underprediction, where the actual journey uses more energy than forecast, leads to range anxiety, with drivers worried about being able to complete their journey. Its opposite, overprediction, when a journey actually uses less range than projected, contributes to time anxiety, as drivers unnecessarily charge their EV or put off trips altogether.
EVs today are poor at estimating how far their battery will take them, and in real-world tests can significantly underestimate or overestimate the energy needed for a journey. Urban driving can be 2 or 3 times as efficient as motorway driving, and yet the vehicle uses the most recent driving efficiency as a guide to the remaining range. This means vehicles can significantly over or underestimate range when cars change from urban to motorway driving, or vice-versa. During Spark’s trial with BP, it was observed that one car could have driven 45 miles more than its displayed range, and on another journey an extra 21 miles more range had to be used to complete the journey than the car predicted. In comparison, Spark intelligent range prediction uses data on where the car is going, not where it has been, and for the same journeys predicted the range to an accuracy of just 3.8 miles and 0.4 miles respectively.
“Our trial with Spark EV helped to increase our understanding of how technology could help reduce consumer range anxiety, especially for new EV drivers,” said Sophia Nadur, Innovation Director, BP. “We now look forward to working together to explore further potential applications into future software iterations.”
The project began as part of BP and RocketSpace’s Mobility Tech Innovation Collaborative programme, which brings together the world’s most promising startups and global industry leaders to work together on paid projects. Previous RocketSpace alumni include Spotify and Uber. Spark was one of just four companies selected globally for the programme, which attracted hundreds of applicants.
“At Spark our mission is to make electric vehicles mainstream by removing barriers to adoption around range and time anxiety,” said Justin Ott, CEO, Spark Technology. “Through our high profile collaboration with BP we have taken the first steps to demonstrate the strength of our unique technology and how it can drive greater uptake of EVs through more accurate range predictions, based on real-world conditions and driving styles. The success of this initial project has opened up major new opportunities for Spark within the automotive sector as we launch our new fundraising round. We look forward to working together further in the future.”