Director, Stanford Precourt Institute for Energy, Professor at Stanford University, Co-founder of Mitra Chem
Importance of using real driving cycles to assess EV battery lifetime In a new paper by Alexis GESLIN, Le Xu, Devi Ganapathi and Kevin Moy (in partnership with Prof. Simona Onori), we systematically compared the effect of realistic driving against laboratory-based discharge cycles on battery aging, the latter being the industry standard when it comes to materials and cell development for lithium-ion batteries. ✅ "Dynamic discharge" (e.g., pulses, rests, regenerative breaking, etc.) leads to substantially longer cycle life when compared constant current discharge, by as much as 40%, for the same C-rate and charging profile. ✅ Using explainable machine learning, we identified key features of dynamic driving cycles that enhance cycle life. ✅ We recommend battery materials and cell developers to use dynamic discharge profiles to assess new chemistries and designs. ✅ Likewise, academics investigating the fundamentals of battery aging should consider dynamic discharge profile as a key lever for aging (alongside C-rate and temperature). ✅ Two years of battery aging data is available publicly as part of this study. This work was carried out at the SLAC-Stanford Battery Center, a joint center between Stanford University and SLAC National Accelerator Laboratory.
Simona Onori
1w
#batteryengineering + #batteryscience = innovation
Great work William Chueh and thank you for publishing the findings. For LinkedIn readers, EV batteries are different than the standard batteries in a common household device and very different versus the grid-scale energy storage batteries paired with renewables. The higher the charge/discharge rate or battery performance the shorter the battery life. EVs need higher performing batteries. Collecting and analyzing real world data is critical for enhancing battery monitoring systems and ultimately improving future batteries. BiaTech Corporation is quite excited about the potential of applied AI for battery management systems and remote monitoring. This has implications for return on investment for last mile commercial deliveries as well as a limiting factor for eVTOL electric vertical take off and landing for Air Taxis and advanced air mobility. #AI #battery #eVTOL #EV #BEV #renewables
Tyler Evans
1w
Great work and thanks to all the authors! In a prior role, my team spent a lot of time using "accelerated" testing or "torture" testing to screen many electrolytes, only to find that in EV-relevant cycling protocols, behavior would look completely different. The best additive package or electrolyte in a torture test might be a poor performer in EV-battery protocols. This is a pertinent discussion for us all to be having.
We did something similar in the context of V2X, working with Stellantis, LG, and NREL on a DoE/CEC program. Here- https://www.epri.com/research/products/000000003002024770
This is an interesting post and paper by William Chuehat Stanford. Indeed, EV OEMs must be able to estimate the cycle life of EV cell and EV batteries pack under real life conditions, which is typically longer than when cycling in traditional testing protocols (100% DOD, CVCC, etc). This is also important when designing the Battery Management System (BMS) software. However, this type of estimation work is in addition to and not instead of the more traditional and standardized testing conditions, which are typically more stringent. For companies that wish to demonstrate the cycle life of specific active materials (for example silicon-graphite anode materials), it is still important to prove with solid data the 100% DOD cycling of full cells with commercial cathodes and EV specs in terms of anode density, inactive material content, first cycle efficiency without prelithiation, normal N/P, etc. Frankly, I see too many material companies cheating in the cycling protocol. Thus, the value of standardized cycling protocols remains very critical when comparing various technologies. The value of more "real life cycling protocols" can then be used by EV OEM to extrapolate further.
Very interesting and thought-provoking result! It makes people rethink about the conventional belief of how batteries should be operated, and bridges the gap between lab test and in-field results.
Really interesting, thank you for sharing! Accessibility of this data is challenging so this is a great advance in the field.
Vivek Lam
1w
Incredible work! Really demonstrates the importance of bridging the gap between real-world use cases and lab testing campaigns!
Director, Stanford Precourt Institute for Energy, Professor at Stanford University, Co-founder of Mitra Chem
1wOpen-access paper and dataset: https://www.nature.com/articles/s41560-024-01675-8