Abstract:
A vehicle may include at least one controller and a battery configured to be selectively charged with energy from an off-board energy source. The at least one controller may be configured to receive user input specifying a cost minimization mode of battery charging. The at least one controller may be further configured to, in response to the input, determine a time period available for charging the battery, determine when, during the time period, a cost of energy from the off-board energy source is at a minimum or below a threshold cost, and cause the battery to be charged during at least a portion of the time period when the cost is at the minimum or below the threshold cost to minimize the cost of charging the battery.

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
       [0001]    This application claims the benefit of U.S. provisional application Ser. No. 61/234,924, filed Aug. 18, 2009, the contents of which are hereby incorporated in their entirety by reference. 
     
    
     STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT 
       [0002]    This invention was made with government support under DE-FC26-08NT04384 awarded by the Department of Energy. The government has certain rights in the invention. 
     
    
     BACKGROUND 
       [0003]    A plug-in hybrid electric vehicle (PHEV) and battery electric vehicle (BEV) may be powered by an electric machine. An on-board battery may store energy for use by the electric machine and be charged with energy from a utility grid or other off-board energy source. The cost of energy from the utility grid may change depending on the time of day. The originating source of the energy (e.g., coal, green energy, such as wind) from the utility grid may also change depending on the time of day. 
       SUMMARY 
       [0004]    A method for charging a vehicle battery with energy from an off-board energy source may include the step of receiving input specifying a cost minimization mode of battery charging. The method may also include, in response to the input, the steps of determining a time period available for charging the battery, determining when, during the time period, a cost of energy from the off-board energy source is at a minimum or below a threshold cost, and causing the battery to be charged during at least a portion of the time period when the cost is at the minimum or below the threshold cost to minimize the cost of charging the battery. 
         [0005]    A method for charging a vehicle battery with energy from an off-board energy source may include the step of receiving user input specifying a green energy mode of battery charging. The method may also include the steps of determining a time period available for charging the battery, determining when, during the time period, energy available from the off-board energy source is identified as being green energy, and causing the battery to be charged during a least a portion of the time period when the energy available from the off-board energy source is identified as being green energy. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0006]      FIG. 1  is a block diagram of portions of an example alternatively powered vehicle. 
           [0007]    Figure is an illustration of an example user interface for the vehicle of  FIG. 1 . 
           [0008]      FIGS. 3A and 3B  are flow charts depicting an example battery charging control algorithm. 
       
    
    
     DETAILED DESCRIPTION 
       [0009]    Faced with increasing environmental and regulatory pressures, utility companies are using price as a way to encourage responsible energy use. Utility pricing, however, may change over the course of a day. For example, utility price tables can vary from 1 cent to 80 cents per kilowatt hour in a single 24 hour period. 
         [0010]    Certain embodiments described herein provide a battery charge optimizer feature that enables a user to, for example, customize battery charging based on user and utility inputs. The optimizer may allow each user to use utility provided pricing information and energy generation source information (via a smart grid interface, for example) to establish a desired optimized battery charge profile based on the user&#39;s wants and needs. 
         [0011]    Three example battery charge optimization choices, in certain embodiments, may be provided: 1) cheapest charge, 2) greenest charge, and 3) fastest charge. In certain cheapest charge embodiments, the vehicle charge time may be based on the cost of electricity. As an example, electricity rates (e.g., utility rate tables from a utility, user selected rates, home energy management system rates, public service rates, or inferred rates, etc.), battery state and battery charge may be used as inputs to algorithms that establish the charge time interval (within optional customer selected time constraints) that minimizes the cost of battery charging. 
         [0012]    In certain greenest charge embodiments, the vehicle charge time may be based on times during which desired energy generation resources (e.g., wind, solar, etc.) are used to generate electricity. As an example, energy generation source information (e.g., utility resource utilization information, home energy management system information, public service information, or inferred information from other data resources, etc.) may be used as input to algorithms that establish the charge time interval (within optional customer selected time constraints) that maximizes the use of “green” generated electricity. 
         [0013]    In certain fastest charge embodiments, the vehicle on-plug time may be minimized to provide the fastest charge, given other customer constraints if selected. These algorithms may determine the total time interval over which the customer selected constraints are evaluated. If no other customer constraints are selected, the fastest charge time may be equivalent to a convenience charge time (e.g., the charge time without use of any optimization algorithms). 
         [0014]    Referring now to  FIG. 1 , an embodiment of an automotive vehicle  10  (e.g., PHEV, BEV) may include a user interface  12  (e.g., touch screen, buttons, dials, etc.), controller(s)  14 , high voltage battery  16  (e.g., traction battery pack, etc.), communications module  18  (e.g., transceiver, power line communications module, etc.), and a powertrain controller(s)  20 . The interface  12 , battery  16 , communications module  18  and powertrain controller(s)  20  are in communication with/under the control of the controller(s)  14 . As known in the art, the battery  16  may provide a source of power to move the vehicle  10 . 
         [0015]    The communications module  18  may communicate with a utility  22  in any suitable/known fashion to obtain, for example, pricing and/or “green” information associated with the energy supplied by the utility. The controller(s)  14  may store this information for later use in determining when to charge the battery  16  as described below. 
         [0016]    Tables 1 and 2 list examples of pricing and “green” information that may be acquired by the controller(s)  14 . 
         [0000]    
       
         
               
             
               
               
               
             
               
               
               
               
             
           
               
                 TABLE 1 
               
             
             
               
                   
               
               
                 Example Pricing and “Green” Utility Information 
               
             
          
           
               
                 TIME 
                 PEAK 
                 GREEN 
               
               
                   
               
             
          
           
               
                 12 
                 AM 
                 0 
                 0 
               
               
                 1 
                 AM 
                 0 
                 0 
               
               
                 2 
                 AM 
                 0 
                 1 
               
               
                 3 
                 AM 
                 0 
                 1 
               
               
                 4 
                 AM 
                 0 
                 0 
               
               
                 5 
                 AM 
                 0 
                 0 
               
               
                 6 
                 AM 
                 0 
                 0 
               
               
                 7 
                 AM 
                 0 
                 0 
               
               
                 8 
                 AM 
                 1 
                 0 
               
               
                 9 
                 AM 
                 1 
                 0 
               
               
                 10 
                 AM 
                 1 
                 1 
               
               
                 11 
                 AM 
                 1 
                 1 
               
               
                 12 
                 PM 
                 1 
                 1 
               
               
                 1 
                 PM 
                 1 
                 1 
               
               
                 2 
                 PM 
                 1 
                 1 
               
               
                 3 
                 PM 
                 1 
                 1 
               
               
                 4 
                 PM 
                 1 
                 1 
               
               
                 5 
                 PM 
                 1 
                 0 
               
               
                 6 
                 PM 
                 1 
                 0 
               
               
                 7 
                 PM 
                 1 
                 0 
               
               
                 8 
                 PM 
                 1 
                 0 
               
               
                 9 
                 PM 
                 0 
                 0 
               
               
                 10 
                 PM 
                 0 
                 0 
               
               
                 11 
                 PM 
                 0 
                 0 
               
               
                   
               
             
          
         
       
     
         [0000]    
       
         
               
             
               
               
               
             
               
               
               
               
             
           
               
                 TABLE 2 
               
             
             
               
                   
               
               
                 Example Pricing and “Green” Utility Information 
               
             
          
           
               
                   
                 PRICE 
                   
               
               
                 TIME 
                 (cents/kWhr) 
                 GREEN 
               
               
                   
               
             
          
           
               
                 12 
                 AM 
                 0.10 
                 0 
               
               
                 1 
                 AM 
                 0.01 
                 0 
               
               
                 2 
                 AM 
                 0.01 
                 1 
               
               
                 3 
                 AM 
                 0.01 
                 1 
               
               
                 4 
                 AM 
                 0.01 
                 0 
               
               
                 5 
                 AM 
                 0.05 
                 0 
               
               
                 6 
                 AM 
                 0.10 
                 0 
               
               
                 7 
                 AM 
                 0.15 
                 0 
               
               
                 8 
                 AM 
                 0.20 
                 0 
               
               
                 9 
                 AM 
                 0.20 
                 0 
               
               
                 10 
                 AM 
                 0.20 
                 1 
               
               
                 11 
                 AM 
                 0.20 
                 1 
               
               
                 12 
                 PM 
                 0.20 
                 1 
               
               
                 1 
                 PM 
                 0.30 
                 1 
               
               
                 2 
                 PM 
                 0.40 
                 1 
               
               
                 3 
                 PM 
                 0.60 
                 1 
               
               
                 4 
                 PM 
                 0.80 
                 1 
               
               
                 5 
                 PM 
                 0.50 
                 0 
               
               
                 6 
                 PM 
                 0.20 
                 0 
               
               
                 7 
                 PM 
                 0.15 
                 0 
               
               
                 8 
                 PM 
                 0.15 
                 0 
               
               
                 9 
                 PM 
                 0.10 
                 0 
               
               
                 10 
                 PM 
                 0.10 
                 0 
               
               
                 11 
                 PM 
                 0.10 
                 0 
               
               
                   
               
             
          
         
       
     
         [0017]    Each of the tables lists the pricing and “green” information by hour. In Table 1, the pricing and “green” information is presented in binary fashion: with regard to pricing, a “1” indicates expensive energy whereas a “0” indicates cheap energy; with regard to “green,” a “1” indicates energy produced via “green” methods such as solar, wind, etc. whereas a “0” indicates energy produced via traditional techniques such as coal, etc. 
         [0018]    Referring now to  FIG. 2 , an example of the user interface  12  is shown in greater detail. Virtual buttons are provided that permit a user to, for example, specify a charge complete time (“ENABLE CHARGE COMPLETE”), specify a charge start time for weekdays and weekends (“ENABLE TIME CHARGE”), specify a price threshold (“ENABLE PRICE CONTROL”), optimize charge settings (“ENABLE OPTIMIZED CHARGE”: “FASTEST,” “CHEAPEST,” “GREENEST”), permit utility interrupt during charging, and request additional information (e.g., battery state of charge, vehicle information, grid information, etc.) In other embodiments, other and/or different features/options may also be provided. 
         [0019]    Referring to  FIGS. 1 and 3A , charge settings are received at operation  24 . For example, the controller(s)  14  may receive information representing the charge settings discussed with reference to  FIG. 2 . At operation  26 , the charge duration is determined. For example, the controller(s)  14  may determine that the duration of time needed to charge the battery  16  (using any suitable/known technique based on for example, current state of charge, desired state of charge, temperature, etc.) is 3 hours. At operation  28 , it is determined whether a charge complete time has been specified. For example, the controller(s)  14  may determine that the user has specified a charge complete time of 8 am. That is, the battery  16  must be recharged by 8 am. 
         [0020]    If it is determined that a charge complete time has been specified, at operation  30 , it is determined whether a charge start time has been specified. For example, the controller(s)  14  may determine that the user has specified a charge start time of 10 pm. That is, the battery  16  cannot begin to be charged until after 10 pm. If it is determined that a charge start time has been specified, the charging window is defined by the charge start time and the charge complete time minus the charge duration at operation  32 . For example, the charging window may be between 10 pm (charge start time) and 5 am (8 am-3 hours charge duration). 
         [0021]    At operation  34 , it is determined whether a price threshold has been specified. For example, the controller(s)  14  may determine that the user has specified that they wish to pay no more than $0.05 per kWhr when the battery  16  is being charged. If it is determined that a price threshold has been specified, the charging window is further defined by the price threshold at operation  36 . For example, the controller(s)  14  will charge the battery  16  during the charging window of 10 pm to 5 am mentioned above only when the price is $0.05 per kWhr or less to the extent possible. 
         [0022]    Returning to operation  28 , if it is determined that a charge complete time has not been specified, at operation  38 , it is determined whether a charge start time has been specified. If it is determined that a charge start time has been specified, the charging window is defined by the charge start time at operation  40 . That is, the charging window has a specified start time but does not have a specified complete time. If it is determined that a charge start time has not been specified, the charging window is undefined. That is, the charging window does not have a specified start or complete time. 
         [0023]    Returning to operation  30 , if it is determined that a charge start time has not been specified, the charging window is defined by the charge complete time minus the charge duration at operation  44 . That is, the charging window has a specified complete time but does not have a specified start time. 
         [0024]    Referring to  FIGS. 1 ,  2  and  3 B, it is determined whether the fastest optimized charge has been selected at operation  46 . For example, the controller(s)  14  may determine whether the user has selected the “FASTEST” button illustrated in  FIG. 2 . If it is determined that the fastest optimized charge has been selected, the charging will be begin at the earliest possible time allowed by the charging window at operation  48 . For example, if the charging window is 10 pm to 5 am, the charging will begin at 10 pm. If it is determined that the fastest optimized charge has not been selected, at operation  50 , it is determined whether the cheapest optimized charge has been selected. For example, the controller(s)  14  may determine whether the user has selected the “CHEAPEST” button illustrated in  FIG. 2 . 
         [0025]    If it is determined that the cheapest optimized charge has been selected, the charging time within the charging window is biased towards the prices cheapest within the charging window at operation  52 . For example, referring to Table 2, if the charging window is 10 pm to 5 am, the cheapest prices are from 1 am to 4 am. The controller(s)  14  will schedule to charge the battery  16  during this time. 
         [0026]    At operation  54 , it is determined whether the greenest optimized charge has been selected. For example, the controller(s)  14  may determine whether the user has selected the “GREENEST” button illustrated in  FIG. 2 . If it is determined that the greenest optimized charge has been selected, the charging time within the charging window will be further biased towards “green” times within the charging window. For example, referring to Table 2, if the charging window is 10 pm to 5 am and the cheapest prices are from 1 am to 4 am, the “green” times within the 1 am to 4 am time frames are 2 am and 3 am. The controller(s)  14  will further schedule to charge the battery  16  during this time. At operation  58 , the battery is charged during the charging window taking into account any biases. 
         [0027]    Returning to operation  50 , if it is determined that the cheapest optimized charge has not been selected, at operation  60 , it is determined whether the greenest optimized charge has been selected. If it is determined that the greenest optimized charge has been selected, the charging time within the charging window will be biased towards “green” times within the charging window at operation  62 . 
         [0028]    Returning to operation  54 , if it is determined that the greenest optimized charge has not been selected, the charging time within the charging window will not be biased towards the “green” times within the charging window at operation  64 . 
         [0029]    Returning to operation  60 , if it is determined that the greenest optimized charge has not been selected, the charging time within the charging window will not be biased towards the cheapest prices or the “green” times within the charging window at operation  66 . 
         [0030]    The control algorithm of  FIGS. 3A and 3B  resolved conflicting constraints by prioritizing them. For example, the charge complete time was given the highest priority while the greenest optimized charge was given the lowest priority. The features contemplated herein, however, may be prioritized in any suitable fashion. As an example, the cheapest optimized charge may be given the highest priority, etc. Additionally, other control algorithms may have different and/or other control features. For example, the greenest optimized charge strategy may be the only feature offered, or the cheapest and greenest optimized charge strategies may be the only features offered, etc. Other scenarios and arrangements are also possible. 
         [0031]    The algorithms (and/or operations) disclosed herein may be deliverable to a processing device, such as the controller(s)  14 ,  20  or any other controller(s)/processing device(s) on-board or off-board the vehicle  24 , in many forms including, but not limited to, (i) information permanently stored on non-writable storage media such as ROM devices and (ii) information alterably stored on writeable storage media such as floppy disks, magnetic tapes, CDs, RAM devices, and other magnetic and optical media. The algorithms may also be implemented in a software executable object. Alternatively, the algorithms may be embodied in whole or in part using suitable hardware components, such as Application Specific Integrated Circuits (ASICs), state machines, controllers or other hardware components or devices, or a combination of hardware, software and firmware components. 
         [0032]    While embodiments of the invention have been illustrated and described, it is not intended that these embodiments illustrate and describe all possible forms of the invention. Rather, the words used in the specification are words of description rather than limitation, and various changes may be made without departing from the spirit and scope of the invention.