18182474. SYSTEMS AND METHODS FOR NEURAL-EXPTANH LEARNED TIRE MODELS simplified abstract (TOYOTA JIDOSHA KABUSHIKI KAISHA)

SYSTEMS AND METHODS FOR NEURAL-EXPTANH LEARNED TIRE MODELS

Organization Name

TOYOTA JIDOSHA KABUSHIKI KAISHA

Inventor(s)

Yan Ming Jonathan Goh of Palo Alto CA (US)

Franck Djeumou of Los Altos CA (US)

SYSTEMS AND METHODS FOR NEURAL-EXPTANH LEARNED TIRE MODELS - A simplified explanation of the abstract

This abstract first appeared for US patent application 18182474 titled 'SYSTEMS AND METHODS FOR NEURAL-EXPTANH LEARNED TIRE MODELS

Simplified Explanation: The patent application describes tire models based on neural-Exp Tanh parameterization for vehicle control.

Key Features and Innovation:

• Incorporates an Exp Tanh function into a control framework for operating a vehicle.
• Utilizes prior slip data, measurements, and a confidence parameter to determine Exp Tanh parameters.
• Estimates tire force using the Exp Tanh function with slip and Exp Tanh parameters.

Potential Applications: This technology can be applied in the automotive industry for improving vehicle control systems and enhancing tire performance.

Problems Solved: Addresses the need for more accurate tire models to optimize vehicle handling and safety.

Benefits:

• Enhanced vehicle control and stability.
• Improved tire performance and longevity.
• Increased safety on the road.

Commercial Applications: Optimizing vehicle control systems for various types of vehicles, including cars, trucks, and motorcycles, to improve overall performance and safety on the road.

Prior Art: Readers can explore prior research on tire modeling, neural networks, and vehicle control systems to understand the background of this technology.

Frequently Updated Research: Stay updated on advancements in neural network technology, tire modeling, and vehicle control systems to enhance the application of this innovation.

Questions about Tire Models Based on Neural-Exp Tanh Parameterization: 1. How does the Exp Tanh function improve tire modeling accuracy? 2. What are the potential implications of this technology on autonomous vehicles?

Original Abstract Submitted

System, methods, and other embodiments described herein relate to tire models based on neural-Exp Tanh parameterization. In one embodiment, a method includes operating a vehicle with a control framework incorporating an Exp Tanh function; calculating prior slip data based on measurements obtained by the control framework; selecting a confidence parameter; using a first predictive model to determine Exp Tanh parameters based upon the prior slip data, the measurements, and the confidence parameter; and inputting a slip parameter and the Exp Tanh parameters into the Exp Tanh function to estimate a tire force.