Tesla, Inc. patent applications on March 14th, 2024

TRIP PLANNING WITH ENERGY CONSTRAINT

Organization Name

tesla, inc.

Inventor(s)

Andrew D. Baglino of San Francisco CA (US)

Thorsten Hayer of Burlingame CA (US)

Brennan Boblett of San Francisco CA (US)

Matthew Fox of Woody Creek CO (US)

Vineet H. Mehta of Mountain View CA (US)

Keijiro Ikebe of Cupertino CA (US)

Kevin Hsieh of Emerald Hills CA (US)

Craig B. Carlson of Los Altos CA (US)

Jeffrey B. Straubel of Menlo Park CA (US)

TRIP PLANNING WITH ENERGY CONSTRAINT - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240085203 titled 'TRIP PLANNING WITH ENERGY CONSTRAINT

Simplified Explanation

The method described in the abstract involves predicting a driver characteristic to determine an energy-versus-distance measure for a planned driving route of a vehicle. This measure is then presented on a user interface associated with the vehicle. The method also involves identifying an already-driven part of the route, determining a model error associated with the energy model based on this information, modifying the energy-versus-distance measure to account for the model error, and presenting the modified measure on the user interface.

• Determining energy-versus-distance measure based on predicted driver characteristic
• Presenting the measure on a user interface
• Identifying already-driven part of the route
• Determining model error associated with the energy model
• Modifying the measure to account for the model error
• Presenting the modified measure on the user interface

Potential Applications

This technology could be applied in:

• Electric vehicles to optimize energy consumption during driving
• Fleet management systems to improve route planning and efficiency

Problems Solved

This technology helps in:

• Reducing energy consumption during driving
• Providing accurate energy predictions for planned routes

Benefits

The benefits of this technology include:

• Increased fuel efficiency
• Enhanced driver awareness of energy consumption
• Improved overall driving experience

Potential Commercial Applications

Potential commercial applications of this technology include:

• Integration into electric vehicle systems
• Incorporation into navigation apps for energy-efficient driving routes

Possible Prior Art

One possible prior art for this technology could be existing energy modeling systems used in electric vehicles or route planning software.

How does this technology handle real-time changes in driving conditions?

The article does not mention how the method adapts to sudden changes in driving conditions that may affect energy consumption.

What data sources are used to predict driver characteristics?

The abstract does not specify the data sources or methods used to predict driver characteristics for determining the energy-versus-distance measure.

Original Abstract Submitted

a method includes: determining, based, at least in part, on a predicted driver characteristic, a first energy-versus-distance measure for a planned driving route of a vehicle, the first energy-versus-distance measure determined using an energy model; presenting the first energy-versus-distance measure on a user interface associated with the vehicle; identifying an already-driven part of the planned driving route; determining, based on information associated with the already-driven part of the planned driving route, a model error associated with the energy model; determining a second energy-versus-distance measure by modifying the first energy-versus-distance measure to account for the model error; and presenting the second energy-versus-distance measure on the user interface associated with the vehicle.