US 11,727,168 B2
Proactive vehicle maintenance scheduling based on digital twin simulations
Takato Masuda, Toyota (JP); BaekGyu Kim, Mountain View, CA (US); and Shinichi Shiraishi, Mountain View, CA (US)
Filed by TOYOTA JIDOSHA KABUSHIKI KAISHA, Toyota (JP)
Filed on Feb. 28, 2018, as Appl. No. 15/908,768.
Prior Publication US 2019/0266295 A1, Aug. 29, 2019
Int. Cl. G06F 30/20 (2020.01); G07C 5/08 (2006.01)
CPC G06F 30/20 (2020.01) [G07C 5/085 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
generating a digital twin of a vehicle associated with an identifier for the vehicle, the digital twin being a digitized version of a real-world vehicle that describes a hardware design and a software design of the vehicle;
receiving digital data describing the vehicle as it exists in a real-world, one or more historical journeys of the vehicle in the real-world, and weather data that describes weather forecasts of future weather events along travel routes included in the one or more historical journeys;
modifying parameters of the digital twin of the vehicle based on the digital data describing the vehicle so that the digital twin is consistent with a depreciated condition of the vehicle as it exists in the real-world;
executing a simulation based on the digital twin and the one or more historical journeys of the vehicle;
estimating that a component of the vehicle will fail at a future time based on the simulation; and
scheduling a reservation to repair the component before the future time so that the component does not fail in the real-world.