Package delivery guidance and assistance system using vehicle sensor data
US-12179782-B2 · Dec 31, 2024 · US
US2018111481A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2018111481-A1 |
| Application number | US-201715784402-A |
| Country | US |
| Kind code | A1 |
| Filing date | Oct 16, 2017 |
| Priority date | Nov 17, 2005 |
| Publication date | Apr 26, 2018 |
| Grant date | — |
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Described herein are devices, systems, and methods for managing the power consumption of an automotive vehicle, and thereby for optimizing the power consumption of the vehicle. The devices and systems for managing the power consumption of the vehicle typically include power management logic that can calculate an applied power for the vehicle engine based on information provided from the external environment of the vehicle, the operational status of the vehicle, one or more command inputs from a driver, and one or more operational parameters of the vehicle.
Opening claim text (preview).
1 . A vehicle comprising: a power train; an electric motor; a drive train; an internal combustion engine; a sensor interface configured to receive sensor data samples during operation of a vehicle; a storage device configured to store said sensor data samples over a number of points in time; and a processing device configured to (i) analyze said sensor data samples stored in said storage device to detect a pattern and (ii) manage energy usage by said electric motor and by said internal combustion engine in response to said pattern, wherein (a) said pattern is used to determine current conditions for said vehicle and (b) said energy usage is managed to enable efficient application of power to said vehicle. 2 . The vehicle according to claim 1 , wherein said energy usage is further managed by adjusting a ratio between said energy usage by said electric motor and said energy usage by said internal combustion engine. 3 . The vehicle according to claim 2 , wherein said ratio is adjusted based on calculated power usage and an amount of energy stored in batteries for said electric motor. 4 . The vehicle according to claim 2 , wherein said ratio is adjusted to use said electric motor while traveling uphill until a power source for said electric motor is empty and recharge said power source for said electric motor while traveling downhill. 5 . The vehicle according to claim 1 , wherein said energy usage is further managed by controlling a consumable power source and a renewable power source. 6 . The vehicle according to claim 5 , wherein (i) said consumable power source comprises gasoline for said internal combustion engine and (ii) said renewable power source comprises a battery for said electric motor. 7 . The vehicle according to claim 5 , wherein said efficient application of said power to said vehicle comprises limiting a usage of said consumable power source. 8 . The vehicle according to claim 1 , wherein said application of said power to said vehicle comprises an amount of acceleration generated by said power train. 9 . The vehicle according to claim 1 , wherein said vehicle is a hybrid electric vehicle. 10 . The vehicle according to claim 9 , wherein said hybrid electric vehicle is configured to be powered by a hydrocarbon fuel and at least one of plugging into an electric grid, converting solar energy and a hydrogen fuel cell. 11 . The vehicle according to claim 1 , wherein (i) said processing device further comprises a classification module, (ii) said sensor data samples are implemented as arrays of data and (iii) said classification module is configured to classify said arrays of data into clusters associated with one or more conditions. 12 . The vehicle according to claim 1 , wherein said sensor data samples are received from one or more sensors configured to monitor said vehicle. 13 . The vehicle according to claim 1 , wherein said sensor data samples are received from one or more sensors configured to monitor an environment external to said vehicle. 14 . The vehicle according to claim 1 , wherein said sensor data samples are received from one or more sensors configured to monitor data from a remote database. 15 . The vehicle according to claim 1 , wherein (i) said sensor data samples are received from one or more driver-related sensors and (ii) said processing device is further configured to generate a likelihood that a particular driver is operating said vehicle based upon said pattern. 16 . The vehicle according to claim 1 , wherein said current conditions comprise at least one of: drag, wind resistance, tire resistance, a location relative to a destination, traffic patterns, an amount of light energy, a position of the sun, geographical information, an elevation of said vehicle, a grade of a road, a location of stoplights, a timing of stoplights, weather, a wind direction, a wind velocity, a temperature, air pressure, moisture, visibility, an amount of vibration, a fuel supply, a battery supply, a condition of tires of said vehicle, a condition of a motor of said vehicle, a condition of said power train of said vehicle, a time of day, a day of the week, a date, and traction. 17 . The vehicle according to claim 1 , wherein said current conditions are determined by deriving inferences from said sensor data samples. 18 . The vehicle according to claim 1 , further comprising a communication device configured to connect to a telemetry system, wherein (i) said vehicle is configured to receive information about a plurality of route segments from said telemetry system and (ii) said processing device is configured to associate said current conditions with said route segments. 19 . The vehicle according to claim 18 , wherein said route segments are used to predict said energy usage.
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