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Researchers at Carnegie Mellon University Use AutoLion to Grasp Battery Aging and Range with AEVs

July 2, 2020

A team of researchers at Carnegie Mellon University used AutoLion battery simulation software to answer a lingering question within the autonomous electric vehicle space; does my range and battery life suffer from the increased energy consumption of the autonomous electric vehicle (AEV) hardware/software? Many OEMs are split in their thinking of how much of an impact this will be. The researchers attempted to understand the uncertainty around this concept. According to the CMU analysis recently published in Nature Energy, they find that the impact could be minimal with energy-efficient computing and an aerodynamic sensor stack. 

This study has great timing as many OEMs across the world are starting to set their own formula when it comes to mixing autonomous capability and electrified vehicles. The researchers attempted to account for the degree of autonomous technology (varying computing load and hardware load) and the vehicle architecture (LiDAR aerodynamic drag or no drag). 

The study began by accounting for various autonomous hardware (cameras and cameras + LiDAR). Then they modeled an electric vehicle from first-principles. Next, the model was used on two velocity profiles (city, highway/suburban) with smoothing for autonomous operation and including sensor and computing loads. Using AutoLion, they accounted for the aging impact to the battery.  

With AutoLion, they determined that the baseline EV would reach the battery end-of-life (80% capacity degradation) in about 110,000 miles. The simulations also showed that AEV with LiDAR reached the end-of-life about 5,000 miles sooner or about 5% more degradation whereas an AEV without LiDAR only had an additional 2% degradation compared to the baseline EV. With GT-AutoLion, OEMs can perform their own study to determine warranty margin, saving them millions of dollars. 

“Having reliable battery degradation models under various use conditions is extremely important.  Thus, being able to quantify what is the loss in odometer range over the lifetime of the vehicle is a valuable metric,” said CMU professor Venkat Viswanathan when asked about the importance of accounting for aging to OEMs. 

The team found that the addition of autonomous capability impacted city driving range by 10% to 15% along with 5% to 10% in a Suburban/Highway route. They find that based on the yearly advancements of battery energy density this decrease in range due to automation has the same effect as a 1 to 2 year lag. 

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