Electric-drive motor vehicles, systems, and control logic for predictive charge planning and powertrain control
US10759298B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 29, 2018 |
| Grant date | Sep 1, 2020 |
| Priority date | — |
| Expiry date | Mar 6, 2039 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02T90/12
- WIPO fieldTransport
- WIPO sectorMechanical engineering
Abstract
Presented are intelligent vehicle systems and control logic for predictive charge planning and powertrain control of electric-drive vehicles, methods for manufacturing/operating such systems, and electric-drive vehicles with smart charge planning and powertrain control capabilities. Systems and methods of AI-based predictive charge planning for smart electric vehicles use machine-learning (ML) driver models that draws on available traffic, location, and roadway map information to estimate vehicle speed and propulsion torque requirements to derive a total energy consumption for a given trip. Systems and methods of AI-based predictive powertrain control for smart hybrid vehicles use ML driver models with deep learning techniques to derive a drive cycle profile defined by a preview route with available traffic, geopositional, geospatial, and map data. ML-generated driver models are developed with collected data to replicate driver behavior and predict the drive cycle profile, including predicted vehicle speed, propulsion torque, and accelerator/brake pedal positions for a preview route.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.