Abstract:
The present invention provides a method for improving fuel economy in hybrid vehicles. More precisely, the method of the present invention includes a selectable “learn mode” in which the vehicle can learn a particular driving schedule. After a particular driving schedule is learned, the schedule can be recalled to optimize fuel economy on future trips following the same route. By recalling a learned schedule, the system knows in advance what energy level will be needed and can proactively charge the hybrid vehicle&#39;s battery to an appropriate level.

Description:
TECHNICAL FIELD  
       [0001]     The present invention relates to a method for improving fuel economy in hybrid vehicles.  
       BACKGROUND OF THE INVENTION  
       [0002]     Hybrid vehicles typically include an engine, a battery and an electric motor/generator. The electric motor/generator is generally operated to power a conventional hybrid vehicle until the battery is discharged by a predetermined amount (e.g., 85% discharged). Thereafter, the engine is operated to power the hybrid vehicle and charge the battery. When the battery is sufficiently charged, the engine is stopped and the electric motor/generator is operated to power the hybrid vehicle in a fuel efficient manner.  
       SUMMARY OF THE INVENTION  
       [0003]     The present invention provides a method for improving fuel economy in hybrid vehicles. More precisely, the method of the present invention includes a selectable “learn mode” in which the vehicle can learn a particular driving schedule. After a particular driving schedule is learned, the schedule can be recalled to optimize fuel economy on future trips following the same route. By recalling a learned schedule, the system knows in advance what energy level will be needed and can proactively charge the hybrid vehicle&#39;s battery to an appropriate level.  
         [0004]     A method of the present invention provides improved fuel efficiency of a hybrid vehicle in the following manner. A control module records energy demand data of the hybrid vehicle during a first trip along a particular driving schedule. Thereafter, the control module recalls the energy demand data prior to a subsequent trip along the same driving schedule. The control module then evaluates the energy demand data to anticipate periods of increased energy demand that require operation of the engine. The control module can then coordinate charging the hybrid vehicle&#39;s battery with the periods of increased energy demand to minimize implementation of the engine such that the fuel efficiency of the hybrid vehicle is improved.  
         [0005]     In one aspect of the present invention, the control module waits to record energy demand data until a signal initiating the learn mode is received.  
         [0006]     In another aspect of the present invention, the control module records the energy demand data at a temporary memory location.  
         [0007]     In yet another aspect of the present invention, the control module saves the recorded energy demand data at a non-volatile memory location.  
         [0008]     In still another aspect of the present invention, the control module waits to recall energy demand data until a signal initiating the recall mode is received.  
         [0009]     The above features and advantages and other features and advantages of the present invention are readily apparent from the following detailed description of the best modes for carrying out the invention when taken in connection with the accompanying drawings. 
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0010]      FIG. 1  is a schematic illustration of hybrid vehicle according to the present invention;  
         [0011]      FIG. 2  is a flow chart illustrating a method for saving energy demand data of the hybrid vehicle of  FIG. 1 ; and  
         [0012]      FIG. 3  is a flow chart illustrating a method for implementing saved energy data to improve the fuel efficiency of the hybrid vehicle of  FIG. 1 . 
     
    
     DESCRIPTION OF THE PREFERRED EMBODIMENTS  
       [0013]     Referring to  FIG. 1 , a schematic depiction of a hybrid vehicle  10  according to the present invention is shown. The hybrid vehicle  10  includes a control module  12  adapted to control an engine  14 , a battery  16  and an electric motor/generator  18 . The engine is adapted to charge the battery  16 , and the battery  16  is adapted to power the electric motor/generator  18 . The electric motor/generator  18  may also charge the battery  16 . The hybrid vehicle  10  further includes a route learn and recall selector  20 .  
         [0014]     The control module  12  preferably includes a microprocessor or CPU  22  and a memory device  24 . The memory device preferably includes RAM  26  and ROM  28 .  
         [0015]     The route learn and recall selector  20  is adapted to initiate learn and recall modes. Accordingly, the selector  20  preferably includes a switch  21  disposed within the passenger compartment of the vehicle  10 , however, the selector  20  may alternatively include other devices adapted to initiate learn and recall modes such as, for example, a driver information center. The “learn mode” is a mode of operation wherein the control module  12  records energy demand characteristics of the hybrid vehicle  10  during a particular route. The “recall mode” is a mode of operation wherein the control module  12  recalls previously recorded energy demand characteristics of the hybrid vehicle  10  during a particular route in order to optimize fuel efficiency as will be described in detail hereinafter.  
         [0016]     A method for saving energy demand data is shown in  FIG. 2 . More precisely,  FIG. 2  shows an algorithm  30  that includes a series of block diagrams representing steps performed by the control module  12 .  
         [0017]     At step  32 , the algorithm  30  determines whether learn mode has been initiated. More precisely, at step  32 , the algorithm  30  determines whether the control module  12  (shown in  FIG. 1 ) has received a signal from the selector  20  (shown in  FIG. 1 ) initiating the learn mode. If the learn mode has not been initiated, the algorithm  30  repeats step  32 . If the learn mode has been initiated, the algorithm  30  proceeds to step  34 . At step  34 , the algorithm  30  begins recording the energy demands of the vehicle  10  (shown in  FIG. 1 ). The energy demand data is preferably recorded in the memory device  24  of the control module  12 . According to a preferred embodiment, the energy demand data is recorded in a temporary memory location such as in RAM  26 , however, the energy demand data may alternatively be recorded in any conventional memory device.  
         [0018]     At step  36 , the algorithm  30  determines whether learn mode has been terminated. More precisely, at step  36 , the algorithm  30  determines whether the control module  12  (shown in  FIG. 1 ) has received a signal from the selector  20  (shown in  FIG. 1 ) terminating the learn mode. If the learn mode has not been terminated, the algorithm  30  returns to step  34 . If the learn mode has been terminated, the algorithm  30  proceeds to step  38 . At step  38 , the algorithm  30  saves the recorded energy demands of the vehicle  10  (shown in  FIG. 1 ). The energy demand data is preferably saved in the memory device  24  of the control module  12 . According to a preferred embodiment, the energy demand data is saved in a non-volatile memory location such as in ROM  28 , however, the energy demand data may alternatively be saved in any conventional memory device. For purposes of the present invention, a “non-volatile” memory location is a memory location that does not require power to retain saved data such that the saved data remains secure after the vehicle  10  is turned off.  
         [0019]     It will be appreciated by one skilled in the art that the energy demand data recorded during a particular driving schedule may be implemented in a variety of different ways to improve the fuel efficiency of a hybrid vehicle during subsequent trips along a substantially similar driving schedule. For purposes of the present invention, a “driving schedule” is defined as a specific route having predefined starting and ending points such as, for example, a driving schedule defined along a specific route between an operator&#39;s home and office. As an example, advanced knowledge of a vehicle&#39;s energy demands would allow maximum implementation of the electric motor/generator  18  by operating the engine  14  only during periods of peak energy demand and simultaneously charging the battery  16  during such periods.  
         [0020]     A method for implementing saved energy demand data to improve fuel economy in a hybrid vehicle according to the present invention is shown in  FIG. 3 . More precisely,  FIG. 3  shows an algorithm  40  that includes a series of block diagrams representing steps performed by the control module  12 . It should be appreciated that  FIG. 3  represents one method for implementing saved energy data to improve fuel economy in a hybrid vehicle, however, alternate methods for improving fuel economy may also be envisioned as will be appreciated by one skilled in the art.  
         [0021]     At step  42 , the algorithm  40  determines whether the recall mode has been initiated. More precisely, at step  42 , the algorithm  40  determines whether the control module  12  (shown in  FIG. 1 ) has received a signal from the selector  20  (shown in  FIG. 1 ) initiating the recall mode. If the recall mode has not been initiated, the algorithm  40  repeats step  42 . If the recall mode has been initiated, the algorithm  40  proceeds to step  44 . At step  44 , the control module  12  determines whether the battery  16  (shown in  FIG. 1 ) is charged less than a predetermined amount. According to a preferred embodiment, the control module  12  determines whether the battery  16  is less that 15% charged at step  44 , however, the “predetermined amount” of step  44  may vary according to alternate embodiments. If the battery  16  is not charged less than a predetermined amount, the algorithm  40  proceeds to step  46 . If the battery  16  is charged less than a predetermined amount, the algorithm  40  proceeds to step  48 . At step  46 , having established that the battery  16  is adequately charged, the algorithm  40  runs the electric motor/generator  18  (shown in  FIG. 1 ) to power the hybrid vehicle  10  (shown in  FIG. 1 ) of the present invention.  
         [0022]     At step  48 , the algorithm  40  determines whether the energy demands of the vehicle  10  (shown in  FIG. 1 ) will exceed a predetermined limit within a predetermined amount of time. More precisely, at step  48 , the microprocessor  22  (shown in  FIG. 1 ) reviews the energy demand data saved in the memory device  24  to see if the energy demands of the vehicle  10  will exceed a predetermined limit within a predetermined amount of time. The predetermined energy demand limit may, for example, be that which exceeds the capacity of the electric motor/generator  18  and therefore requires operation of the engine  14 . Both the predetermined energy demand limit and the predetermined amount of time may vary as required to meet the needs of a particular application. If the energy demands of the vehicle  10  will exceed a predetermined limit within a predetermined amount of time, the algorithm  40  proceeds to step  50 . If the energy demands of the vehicle  10  will not exceed a predetermined limit within a predetermined amount of time, the algorithm  40  proceeds to step  52 .  
         [0023]     At step  50 , the algorithm  40  checks to ensure the battery  16  (shown in  FIG. 1 ) is sufficiently charged to power the vehicle  10  during the predetermined amount of time established at step  48 . If the battery  16  is sufficiently charged, the algorithm  40  waits the predetermined amount of time at step  50  and proceeds to step  52 . At step  52 , the engine  14  is operated to power the vehicle  10  and to charge the battery  16 . After step  52 , the algorithm  40  returns to step  44 .  
         [0024]     A conventional hybrid vehicle would automatically run the engine to charge the battery at step  48  whenever the battery is less than a predetermined amount charged (e.g., less than 15%). Thereafter, the conventional hybrid vehicle would run the engine again to address any increased energy demands. This conventional mode of operation may unnecessarily run the engine to charge the battery when the battery would otherwise be completely charged during subsequent periods of increased energy demand. It can therefore be seen that by delaying the operation of the engine  14  until it is absolutely necessary, the engine  14  may be operated less frequently thereby improving the fuel efficiency of the hybrid vehicle  10 .  
         [0025]     While the best modes for carrying out the invention have been described in detail, those familiar with the art to which this invention relates will recognize various alternative designs and embodiments for practicing the invention within the scope of the appended claims.