20240085203.TRIP PLANNING WITH ENERGY CONSTRAINT simplified abstract (tesla, inc.)

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 presented on a user interface, and any model errors associated with the energy model are identified and accounted for in a modified energy-versus-distance measure.

• Determining energy consumption for a driving route based on predicted driver characteristic
• Presenting energy consumption information on a user interface
• Modifying energy consumption calculation to adjust for model errors

Potential Applications

This technology could be applied in:

• Electric vehicle range estimation
• Fuel efficiency optimization for traditional vehicles

Problems Solved

This technology addresses:

• Inaccurate energy consumption predictions
• Lack of real-time feedback on driving efficiency

Benefits

The benefits of this technology include:

• Improved accuracy in energy consumption estimates
• Enhanced driver awareness of driving efficiency

Potential Commercial Applications

A potential commercial application for this technology could be:

• Integration into vehicle navigation systems for energy-efficient route planning

Possible Prior Art

One possible prior art could be:

• Existing vehicle energy management systems that provide real-time feedback on energy consumption.

How does this technology handle variations in driving conditions?

The technology may need to incorporate real-time data on driving conditions to adjust energy consumption estimates accordingly.

What impact does this technology have on overall vehicle performance?

It would be important to understand how the modifications to energy consumption calculations affect the overall performance and efficiency of the vehicle.

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.