The subject invention relates to systems and methods for providing vehicle related feedback and, more particularly, to a vehicular feedback systems and methods that provide carbon dioxide feedback.
Vehicles with advanced propulsion systems are typically viewed by consumers as an environmentally-friendly alternative to vehicles with traditional internal combustion engines. As such, these hybrid and electric vehicles are often thought of as being ‘green.’ Automobile manufacturers have displayed biological displays (ex. Leaf symbols) in a variety of forms to reinforce this connection.
While existing displays are attractive for marketing campaigns and offer the consumer some feedback related to their driving behaviors, they do not provide feedback to the consumer regarding their actual carbon dioxide emissions. In addition, monitoring user driving habits typically comprises an inefficient process with little flexibility. A user that desires to optimize his/her driving habits to minimize waste (e.g., fuel, cost, carbon dioxide emissions, etc.) may review reading materials that guide or specify to a user on ways of optimizing ones driving habits. However, these reading materials can be difficult to obtain. Once obtained, reviewing these materials can be time consuming and costly.
Accordingly, it is desirable to provide consumers with feedback as to how they have reduced their carbon dioxide emissions in terms that continue to reinforce the link between advanced propulsion systems and environmental stewardship.
In one exemplary embodiment of the present invention a method of providing carbon dioxide feedback in a computer system is provided. The method includes computing an amount of carbon dioxide avoided by a vehicle at a processor, calculating a number of equivalent trees based on the computation, and displaying the number of equivalent trees on a display device.
In another exemplary embodiment of the present invention a carbon dioxide feedback system is provided. The system includes a computer memory; and one or more processors in communication with the computer memory, the one or more processors configured to perform a method comprising: computing an amount of carbon dioxide avoided by a vehicle; calculating a number of equivalent trees based on the computation; and generating display signals that display the number of equivalent trees on a display device.
The above features and advantages and other features and advantages of the invention are readily apparent from the following detailed description of the invention when taken in connection with the accompanying drawings.
Other objects, features, advantages and details appear, by way of example only, in the following detailed description of embodiments, the detailed description referring to the drawings in which:
The following description is merely exemplary in nature and is not intended to limit the present disclosure, its application or uses. It should be understood that throughout the drawings, corresponding reference numerals indicate like or corresponding parts and features. As used herein, the term module refers to an application specific integrated circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or group) and memory that executes one or more software or firmware programs, one or more software or firmware programs, a combinational logic circuit, and/or other suitable components that provide the described functionality.
Referring now to
The sensing devices 112 sense operating conditions of the vehicle 110. In various embodiments, the sensing devices 112 are an integral part of one or more components or subsystems of the vehicle 110 or are mounted directly or indirectly on the vehicle 110 or parts thereof. In various other embodiments, one or more of the sensing devices 112 are in signal communication (e.g., via cables, connecting harness, wirelessly, etc.) with the vehicle 110.
The computing module 114 receives signals from the sensing devices 112 and computes carbon dioxide (CO2) performance and reduction values and other vehicle related information. In various embodiments, the computing module 114 utilizes these values to estimate CO2 feedback data and communicates the data to a display 116 to provide graphical or textual feedback to a user. The feedback provides information to the user about how his/her driving habits contribute to CO2 reduction. In various embodiments, the computing module 114 can provide carbon dioxide feedback by determining wasteful driving habits. The carbon dioxide feedback can be presented to the user in a pictorial or graphical form. For example, the carbon dioxide feedback can be presented to the user in the form of trees affected by the driving habit.
In one example, the computing module 114 may evaluate a driving habit such as vehicle braking force applied immediately after an acceleration event (e.g., within 60 seconds) and may calculate the CO2 representing this amount of energy (whether the vehicle is electric or gas operated at that moment). This calculation provides the user with the amount of CO2 needlessly generated. As can be appreciated, the computing module 114 can perform an analysis of other driving habits and is not limited to the present example.
As can be appreciated, the computing module 114 and/or the display 116 can be an integral part of one or more components or subsystems of the vehicle 110 or can be external to the vehicle 110. For example, the computing module 114 can be implemented in one of the control modules (not shown) of the vehicle 110 or can be implemented in a computer, laptop, server, personal handheld device, or any other computing device having a processor and memory.
In various embodiments, when the computing module 114 is part of the vehicle 110, the computing module 114 can communicate the feedback values through a network 118 to an external computing module 120. The network 118 can be any type, or a combination thereof, of known networks including, but not limited to, a wide area network (WAN), a local area network (LAN) such as, for example, the Internet, Intranet(s), and/or wireless communication network(s). The external computing module 120 can be any computing device having a processor and memory, including, but not limited to, a computer, a laptop, a server, a personal handheld device, and can similarly communicate the feedback values to a display 122 to provide pictorial, graphical, or textual feedback to a user.
Referring now to
In various embodiments, the computing module 114 includes a CO2 computation module 130, a tree estimation module 132, and a display module 134. The computation module 130 computes carbon dioxide performance and reduction values 136 based on vehicle related data 138 and one or more algorithms. As can be appreciated, the calculation of CO2 performance and reduction can be based on the various engine types of other vehicles comparable to the vehicle 110. For example, the CO2 feedback can be based on a vehicle comparison model that identifies the CO2 performance and reduction on various vehicle models and is not limited to the vehicle being driven (e.g., vehicle 110). As such, the computation module 130 can identify how the vehicle 110 compares to other vehicles with respect to its impact on the environment, particularly its CO2 contribution or reduction.
In various embodiments, the computation module 130 computes an amount of CO2 generation (e.g. lbs of CO2) avoided using one or more algorithms/equations. In an exemplary embodiment, the amount (lbs) of CO2 generation avoided is calculated using the following equation:
CO2 avoided=EM*FE*Kg*2.2. (1)
Where, EM represents the electric mileage. FE represents the fuel economy for an equivalent gas engine. Kg represents the kilograms of CO2 in one liter of gasoline, and 2.2 is the conversion to pounds. Of course, variations of equation 1 can be used to calculate the amount of CO2 generation avoided, such as, for example, using various conversion factors. In this equation, assumptions are made, such as, for example, 1 liter of gasoline is equal to 2360 g CO2, and a 1.4 liter internal combustion engine is capable of a fuel economy of 5.5 L/100 kilometers (km). Of course, these assumptions can vary based on various factors. For example, the fuel economy for an equivalent ICE of another vehicle can be used to compute the amount of CO2 generation avoided.
The tree estimation module 132 estimates a number of trees 140 that may be affected based on the carbon dioxide performance and reduction values 136. For example, the tree estimation module 132 estimates a number of equivalent trees planted based on the amount of CO2 generation avoided by the vehicle 110 using one or more algorithms/equations. For example, the number of equivalent trees planted can be estimated using the following equation:
No of Trees=CO2 avoided*average CO2 sequestered by mature tree. (2)
Of course, variations of equation 2 can be used to compute the number of trees planted. In this equation, assumptions are made, such as, for example, the average CO2 sequestered by a mature tree is equal to 50 pounds.
The display module 134 generates display signals 142, including feedback data based on the estimated number of trees 140, to the display 116 (
In addition to the tree information, the feedback data can further include, the carbon dioxide performance and reduction values 136. For example, the values can include, but are not limited to, non-electric mileage (kilometers (km)), electric mileage (km), CO2 emissions (grams), the lbs of CO2 generation avoided, fuel saved (liters ((L)), costs saved ($), mileage per trip, charge (kilowatt-hour (kWh), cost for electricity (based on $0.091/kwh), and cost per trip (based on $1.00/L), or any combination thereof. The units and values described herein can vary depending on the application. Various conversion factors can be used to obtain the desired units. Although the data described herein is in the metric standard, other systems of units can be used.
In an exemplary embodiment, the display module 134 generates display signals 142 and receives user input signals 144 that allows the user to select what data to view or compute through a graphical user interface (GUI). For example, the display module 134 generates GUIs that allow the user to select other competitor vehicles with an equivalent ICE to be used in computing the number of equivalent trees 140 or generate a vehicle comparison model.
With reference now to
In one example, the method may begin at 200. At 210, determine electric mileage of the vehicle 110 using one or more existing algorithms. The driving habits detected by the sensing devices 112 may modify the electric mileage value as described above. At block 220, select a comparison engine type. Alternately, the comparison engine type is predefined or preselected. In an exemplary embodiment, the user selects one of many different equivalent engine types using a GUI. At 230, determine the fuel economy for the engine type selected or predefined. Next, apply one or more algorithms that use the electric mileage and the selected or preselected fuel economy as inputs at 240. As a result, the number of equivalent trees planted is determined at block 250. Signals are generated based on the number of trees and/or CO2 values at 260 and the method may end at 270.
While the invention has been described with reference to exemplary embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the invention without departing from the essential scope thereof. Therefore, it is intended that the invention not be limited to the particular embodiments disclosed as the best mode contemplated for carrying out this invention, but that the invention will include all embodiments falling within the scope of the present application.
This patent application claims priority to U.S. Provisional Patent Application Ser. No. 61/313,510 filed Mar. 12, 2010, which is incorporated herein by reference in its entirety.
Number | Name | Date | Kind |
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20060184445 | Sandor et al. | Aug 2006 | A1 |
20110145438 | Sakamoto | Jun 2011 | A1 |
Number | Date | Country | |
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20110224854 A1 | Sep 2011 | US |
Number | Date | Country | |
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61313510 | Mar 2010 | US |