Patent Publication Number: US-2016243958-A1

Title: Vehicle inclination based battery state of charge target

Description:
TECHNICAL FIELD 
     This application generally relates to energy management for hybrid vehicles. 
     BACKGROUND 
     A hybrid-electric vehicle includes a traction battery constructed of multiple battery cells in series and/or parallel. The fraction battery provides power for vehicle propulsion and accessory features. During operation, the traction battery may be charged or discharged based on the operating conditions including a battery state of charge (SOC), driver demand and regenerative braking 
     SUMMARY 
     A battery management system for a vehicle includes a battery and a controller. The controller is programmed to set a state of charge (SOC) target for the battery according to an angle of inclination and speed of the vehicle. The controller is programmed to discharge the battery to achieve the target in response to a SOC of the battery being greater than the target and the speed being greater than a threshold. 
     A method of operating a hybrid vehicle having a traction battery includes setting by a controller a state of charge (SOC) target for the battery according to an angle of inclination and a speed of the vehicle, and discharging the battery when a SOC of the battery is greater than the target and the speed is greater than a threshold. 
     A hybrid vehicle includes a traction battery, a powertrain coupled to the battery, and a controller. The controller is programmed to set a state of charge (SOC) target for the battery according to losses associated with the powertrain and an angle of inclination of the vehicle. The controller is programmed to respond to a SOC of the battery and a speed of the vehicle. When the SOC is greater than the target and the speed is greater than a threshold, the controller is programmed to discharge the battery to achieve the target. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is an exemplary diagram of a hybrid vehicle illustrating typical drivetrain and energy storage components. 
         FIG. 2  is an exemplary diagram of a battery pack controlled by a Battery Energy Control Module. 
         FIG. 3  is an exemplary flow diagram illustrating a target SOC computation for vehicle operation based on electric power. 
         FIG. 4A  is an exemplary graph that illustrates battery state of charge, vehicle speed and internal combustion engine operation in relation to time. 
         FIG. 4B  is an exemplary graph that illustrates battery state of charge, vehicle speed and internal combustion engine operation in relation to time such that the internal combustion engine operation is adjusted to maximize EV duration. 
         FIG. 5A  is an exemplary graph that illustrates an internal combustion engine start point in relation to driver power demand, battery state of charge and vehicle speed. 
         FIG. 5B  is an exemplary graph that illustrates an internal combustion engine shut-off point in relation to driver power demand, battery state of charge and vehicle speed. 
         FIG. 5C  is an exemplary graph that illustrates hysteresis between an internal combustion engine starting point and shut-off point in relation to driver power demand, battery state of charge and vehicle speed. 
         FIG. 5D  is an exemplary graph that illustrates an internal combustion engine shut-off point in relation to driver power demand, battery state of charge and vehicle speed, such that an engine operational time is increased to provide a greater charge to the battery. 
         FIG. 6  is an exemplary flow diagram illustrating a target SOC computation for vehicle operation based on an available regenerative energy. 
         FIG. 7  is an exemplary graph that illustrates an internal combustion engine start point in relation to driver power demand, battery state of charge and an available regenerative energy. 
         FIG. 8  is an exemplary flow diagram illustrating a grade-based target SOC computation for vehicle operation. 
         FIG. 9A  is an exemplary graph that illustrates battery state of charge and internal combustion engine operation in relation to time and further in relation to vehicle speed or road grade. 
         FIG. 9B  is an exemplary graph that illustrates battery state of charge and internal combustion engine operation in relation to time and further in relation to vehicle speed or road grade, such that the internal combustion engine operation is maximized to capture available regenerative energy. 
     
    
    
     DETAILED DESCRIPTION 
     Embodiments of the present disclosure are described herein. It is to be understood, however, that the disclosed embodiments are merely examples and other embodiments can take various and alternative forms. The figures are not necessarily to scale; some features could be exaggerated or minimized to show details of particular components. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a representative basis for teaching one skilled in the art to variously employ the present invention. As those of ordinary skill in the art will understand, various features illustrated and described with reference to any one of the figures can be combined with features illustrated in one or more other figures to produce embodiments that are not explicitly illustrated or described. The combinations of features illustrated provide representative embodiments for typical applications. Various combinations and modifications of the features consistent with the teachings of this disclosure, however, could be desired for particular applications or implementations. 
       FIG. 1  depicts a typical plug-in hybrid-electric vehicle (PHEV) having a powertrain or powerplant that includes the main components that generate power and deliver power to the road surface for propulsion. A typical plug-in hybrid-electric vehicle  12  may comprise one or more electric machines  14  mechanically connected to a hybrid transmission  16 . The electric machines  14  may be capable of operating as a motor or a generator. In addition, the hybrid transmission  16  is mechanically connected to an internal combustion engine  18  also referred to as an ICE or engine. The hybrid transmission  16  is also mechanically connected to a drive shaft  20  that is mechanically connected to the wheels  22 . The electric machines  14  can provide propulsion and deceleration capability when the engine  18  is turned on or off. The electric machines  14  also act as generators and can provide fuel economy benefits by recovering energy that would normally be lost as heat in the friction braking system. The electric machines  14  may also reduce vehicle emissions by allowing the engine  18  to operate at more efficient speeds and allowing the hybrid-electric vehicle  12  to be operated in electric mode with the engine  18  off under certain conditions. A powertrain has losses that may include transmission losses, engine losses, electric conversion losses, electric machine losses, electrical component losses and road losses. These losses may be attributed to multiple aspects including fluid viscosity, electrical impedance, vehicle rolling resistance, ambient temperature, temperature of a component, and duration of operation. 
     A fraction battery or battery pack  24  stores energy that can be used by the electric machines  14 . A vehicle battery pack  24  typically provides a high voltage DC output. The traction battery  24  is electrically connected to one or more power electronics modules  26 . One or more contactors  42  may isolate the traction battery  24  from other components when opened and connect the traction battery  24  to other components when closed. The power electronics module  26  is also electrically connected to the electric machines  14  and provides the ability to bi-directionally transfer energy between the traction battery  24  and the electric machines  14 . For example, a typical traction battery  24  may provide a DC voltage while the electric machines  14  may operate using a three-phase AC current. The power electronics module  26  may convert the DC voltage to a three-phase AC current for use by the electric machines  14 . In a regenerative mode, the power electronics module  26  may convert the three-phase AC current from the electric machines  14  acting as generators to the DC voltage compatible with the traction battery  24 . The description herein is equally applicable to a pure electric vehicle. For a pure electric vehicle, the hybrid transmission  16  may be a gear box connected to an electric machine  14  and the engine  18  may not be present. 
     In addition to providing energy for propulsion, the traction battery  24  may provide energy for other vehicle electrical systems. A typical system may include a DC/DC converter module  28  that converts the high voltage DC output of the traction battery  24  to a low voltage DC supply that is compatible with other vehicle loads. Other high-voltage loads  46 , such as compressors and electric heaters, may be connected directly to the high-voltage without the use of a DC/DC converter module  28 . The low-voltage systems may be electrically connected to an auxiliary battery  30  (e.g., 12V battery). 
     The vehicle  12  may be an electric vehicle or a plug-in hybrid vehicle in which the traction battery  24  may be recharged by an external power source  36 . The external power source  36  may be a connection to an electrical outlet that receives utility power. The external power source  36  may be electrically connected to electric vehicle supply equipment (EVSE)  38 . The EVSE  38  may provide circuitry and controls to regulate and manage the transfer of energy between the power source  36  and the vehicle  12 . The external power source  36  may provide DC or AC electric power to the EVSE  38 . The EVSE  38  may have a charge connector  40  for plugging into a charge port  34  of the vehicle  12 . The charge port  34  may be any type of port configured to transfer power from the EVSE  38  to the vehicle  12 . The charge port  34  may be electrically connected to a charger or on-board power conversion module  32 . The power conversion module  32  may condition the power supplied from the EVSE  38  to provide the proper voltage and current levels to the traction battery  24 . The power conversion module  32  may interface with the EVSE  38  to coordinate the delivery of power to the vehicle  12 . The EVSE connector  40  may have pins that mate with corresponding recesses of the charge port  34 . Alternatively, various components described as being electrically connected may transfer power using a wireless inductive coupling. 
     One or more wheel brakes  44  may be provided for decelerating the vehicle  12  and preventing motion of the vehicle  12 . The wheel brakes  44  may be hydraulically actuated, electrically actuated, or some combination thereof. The wheel brakes  44  may be a part of a brake system  50 . The brake system  50  may include other components to operate the wheel brakes  44 . For simplicity, the figure depicts a single connection between the brake system  50  and one of the wheel brakes  44 . A connection between the brake system  50  and the other wheel brakes  44  is implied. The brake system  50  may include a controller to monitor and coordinate the brake system  50 . The brake system  50  may monitor the brake components and control the wheel brakes  44  for vehicle deceleration. The brake system  50  may respond to driver commands and may also operate autonomously to implement features such as stability control. The controller of the brake system  50  may implement a method of applying a requested brake force when requested by another controller or sub-function. 
     One or more electrical loads  46  or auxiliary electric loads may be connected to the high-voltage bus. The electrical loads  46  may have an associated controller that operates and controls the electrical loads  46  when appropriate. Examples of auxiliary electric loads or electrical loads  46  include a battery cooling fan, an electric air conditioning unit, a battery chiller, an electric heater, a cooling pump, a cooling fan, a window defrosting unit, an electric power steering system, an AC power inverter, and an internal combustion engine water pump. 
     The various components discussed may have one or more associated controllers to control and monitor the operation of the components. The controllers may communicate via a serial bus (e.g., Controller Area Network (CAN), Ethernet, Flexray) or via discrete conductors. A system controller  48  may be present to coordinate the operation of the various components. 
     A traction battery  24  may be constructed from a variety of chemical formulations. Typical battery pack chemistries may be lead acid, nickel-metal hydride (NIMH) or Lithium-Ion.  FIG. 2  shows a typical traction battery pack  24  in a series configuration of N battery cells  72 . Other battery packs  24 , however, may be composed of any number of individual battery cells connected in series or parallel or some combination thereof. A battery management system may have a one or more controllers, such as a Battery Energy Control Module (BECM)  76  that monitors and controls the performance of the traction battery  24 . The BECM  76  may include sensors and circuitry to monitor several battery pack level characteristics such as pack current  78 , pack voltage  80  and pack temperature  82 . The BECM  76  may have non-volatile memory such that data may be retained when the BECM  76  is in an off condition. Retained data may be available upon the next key cycle. 
     In addition to the pack level characteristics, there may be battery cell level characteristics that are measured and monitored. For example, the terminal voltage, current, and temperature of each cell  72  may be measured. The battery management system may use a sensor module  74  to measure the battery cell characteristics. Depending on the capabilities, the sensor module  74  may include sensors and circuitry to measure the characteristics of one or multiple of the battery cells  72 . The battery management system may utilize up to N c  sensor modules or Battery Monitor Integrated Circuits (BMIC)  74  to measure the characteristics of all the battery cells  72 . Each sensor module  74  may transfer the measurements to the BECM  76  for further processing and coordination. The sensor module  74  may transfer signals in analog or digital form to the BECM  76 . In some embodiments, the sensor module  74  functionality may be incorporated internally to the BECM  76 . That is, the sensor module hardware may be integrated as part of the circuitry in the BECM  76  and the BECM  76  may handle the processing of raw signals. 
     The BECM  76  may include circuitry to interface with the one or more contactors  42 . The positive and negative terminals of the traction battery  24  may be protected by contactors  42 . 
     Battery pack state of charge (SOC) gives an indication of how much charge remains in the battery cells  72  or the battery pack  24 . The battery pack SOC may be output to inform the driver of how much charge remains in the battery pack  24 , similar to a fuel gauge. The battery pack SOC may also be used to control the operation of an electric or hybrid-electric vehicle  12 . Calculation of battery pack SOC can be accomplished by a variety of methods. One possible method of calculating battery SOC is to perform an integration of the battery pack current over time. This is well-known in the art as ampere-hour integration. 
     Battery SOC may also be derived from a model-based estimation. The model-based estimation may utilize cell voltage measurements, the pack current measurement, and the cell and pack temperature measurements to provide the SOC estimate. 
     The BECM  76  may have power available at all times. The BECM  76  may include a wake-up timer so that a wake-up may be scheduled at any time. The wake-up timer may wake up the BECM  76  so that predetermined functions may be executed. The BECM  76  may include non-volatile memory so that data may be stored when the BECM  76  is powered off or loses power. The non-volatile memory may include Electrical Eraseable Programmable Read Only Memory (EEPROM) or Non-Volatile Random Access Memory (NVRAM). The non-volatile memory may include FLASH memory of a microcontroller. 
     When operating the vehicle, actively modifying the way battery SOC is managed can yield higher fuel economy or longer EV-mode (electric propulsion) operation, or both. The vehicle controller must conduct these modifications at both high SOC and low SOC. At low SOC, the controller can examine recent operating data and decide to increase SOC via opportunistic engine-charging (opportunistic means to do this if the engine is already running) This is done to provide longer EV-mode operation when the engine turns off. Conversely, at high SOC, the controller can examine recent operating data and other data (location, temperature, etc) to reduce SOC via EV-mode propulsion, reduced engine output, or auxiliary electrical loads. This is done to provide higher battery capacity to maximize energy capture during an anticipated regenerative braking event, such as a high-speed deceleration or hill descent. 
       FIG. 3  is an exemplary flow diagram  300  illustrating a method of modifying battery management parameters when the battery has a low SOC. The change in battery management may increase vehicle operation based on electricity alone or improve engine efficiency, or both. The figure shows a target SOC computation for vehicle operation based on electric power. Historical data is input in block  302  in which the historical data includes a recent battery SOC or a battery SOC histogram, an auxiliary electric load, a vehicle speed, recent vehicle operation based on electricity only, or driver behavior. The auxiliary electric loads include a battery cooling fan, an electric air conditioning unit, a battery chiller, an electric heater, a cooling pump, a cooling fan, a window defrosting unit, an electric power steering system, an AC power inverter, and an internal combustion engine water pump. Also, present and future data is input in block  302 . The present data includes an auxiliary electric load and a vehicle speed. The future data includes estimated duration of vehicle operation based on electricity only and road grade also referred to as slope or changes in elevation. Relating to road grade is the angle of inclination which is the angle between the longitudinal plane of the vehicle and earth&#39;s horizontal plane. The angle of inclination may be determined by multiple means including an output of an inclinometer or a combination of wheel speed sensor output indicative of acceleration along a longitudinal plane of the vehicle and longitudinal accelerometer output indicative of an acceleration along the longitudinal plane as affected by gravity. 
     An estimated duration of vehicle operation based on electricity only is calculated in block  304 . The estimated duration of vehicle operation based on electricity only calculated in  304  and the battery SOC are compared against a threshold values in block  306 . If the estimated duration of vehicle operation based on electricity only is less than a first threshold and the battery SOC is less than a second threshold, a target SOC is adjusted or a current limit is adjusted in block  308 . 
     The adjustment of the target SOC may include an increase to a target SOC such that when an internal combustion engine (ICE) is operating, the operation time may be increased or the energy output from the ICE may be increased, or both. The increase in operation time or output energy may be to support battery charging, thus allowing the battery to supply electrical energy for a longer duration when the vehicle operates on electricity only (i.e., EV mode). Also, the energy generation may be optimized based on a brake specific fuel consumption map of the ICE. This may result in greater fuel efficiency during the total vehicle trip. 
       FIG. 4A  is an exemplary graph  400  that illustrates battery state of charge  404 , vehicle speed  402  and internal combustion engine operation  406  in relation to time. When the vehicle begins operation from a stopped position, the vehicle acceleration may use battery power or power from an internal combustion engine (ICE), or both. An example of vehicle acceleration is shown during the time  410 . After the vehicle accelerated, it achieved a travel speed. The travel speed in this example is a vehicle speed in which the vehicle is capable of being propelled by electricity only. At this speed, typically, the battery SOC will toggle around a target battery SOC having charging time periods  412  in which the ICE is operating to charge the battery, and discharging time periods  414  in which the ICE is shut-off and the vehicle operation is by battery alone. For a consumer these short periods of EV-mode may dissatisfy the driver, as many hybrid vehicle consumers desire long periods of EV operation. 
       FIG. 4B  is an exemplary graph  420  that illustrates battery state of charge  424 , vehicle speed  422  and internal combustion operation  426  in relation to time  428  in which an internal combustion engine operation  426  is adjusted to maximize EV duration. Here like in  FIG. 4A , the vehicle is accelerated from a stop. But, after reaching the travel speed, being a vehicle speed in which the vehicle is capable of being propelled by electricity only, a controller increases the SOC threshold at which the engine shuts off such that the engine continues to charge the battery and increase the battery state of charge  424 . The vehicle may operate the internal combustion engine (ICE) for a time  430  greater than a time  412 , such that the ensuing electric vehicle only operation occurs for a time  432  greater than a time  414 . Also, the vehicle may operate the engine at a speed, a torque, and a fuel consumption rate that maximizes power output with respect to the fuel consumption rate. The controller may choose an engine operating point based on data from a brake specific fuel consumption (BSFC) table, wherein the engine operates at a fuel consumption greater than a minimum fuel consumption thus increasing a current flowing from the generator to the battery. This may increase an engine operational hysteresis also referred to as just a hysteresis to alleviate the typical engine cycling also referred to as toggling on and off around a typical battery SOC operating range or set point. 
       FIG. 5A  is an exemplary graph  500  that illustrates an internal combustion engine starting threshold  508  in relation to driver power demand  506 , battery state of charge  502  and vehicle speed  504 . For a given vehicle speed and battery SOC, the graph shows the amount of driver-demanded power above which an engine start will occur. For example, when the battery SOC is low and vehicle speed is low, a relatively low amount of driver-demanded power is required to start the engine. When the engine is operating, the output power can be used to drive the wheels, to generate electricity via connection to generator, or to provide output to other auxiliary components. 
       FIG. 5B  is an exemplary graph  525  that illustrates an internal combustion engine shut-off threshold  510  in relation to driver power demand  506 , battery state of charge  502  and vehicle speed  504 . For a given vehicle speed and battery SOC, the graph shows the amount of driver-demanded power below which the engine is shut off. For example, when SOC is high and vehicle speed is low, a relatively high level of driver-demanded power will allow the engine to shut off. When the engine is off, the vehicle can be propelled electrically or decelerated using the friction and regenerative brake system. 
       FIG. 5C  is an exemplary graph  530  that illustrates hysteresis  512  between an internal combustion engine starting point  508  and shut-off point  510  in relation to driver power demand  506 , battery state of charge  502  and vehicle speed  504 . 
       FIG. 5D  is an exemplary graph  535  that illustrates a modified internal combustion engine shut-off threshold  520  in relation to driver power demand  506 , battery state of charge  502  and vehicle speed  504 , which results in longer engine operation so that the battery may be charged more before entering EV-mode. 
     In contrast to the battery control method described in  FIGS. 4-5 ,  FIG. 6  is an exemplary flow diagram  600  illustrating a method of modifying battery management at high SOC, in relation to a vehicle speed, in order to ensure enough battery capacity to maximize energy capture during an imminent regenerative braking event. The diagram shows a target SOC computation for vehicle operation based on an available regenerative energy. In block  602  a road load is calculated based on historical data. An example calculation is shown in equation 1 
         F   loss,parasitic   =ma−mg sin θ− (F regen   +F   friction )   (1)
 
     in which, for a given point in time, m is the vehicle mass, a is the vehicle acceleration/deceleration, g is the gravitational constant, sing is a road grade factor, F regen  is the estimated force applied to vehicle deceleration from the regenerative brake system, and F friction  is the estimated force applied to vehicle deceleration from the friction brake system. For a given set of vehicle operation data, the parasitic forces acting on the vehicle can be estimated through regressive data fitting or other means, as is known in the art. An alternative form of equation 1 is shown in equation 2 
         E   loss,parasitic   =F   loss,parasitic   d=E   kinetic   −E   grade −(E regen   +E   friction )   (2)
 
     in which E loss,parasitic  is an energy loss associated with a parasitic force F toss,parasitic  over a distance d, F kinetic  is a kinetic energy of the vehicle over the distance, E regen is  a potential regenerative energy capable of being captured over the distance, and E friction  is a friction braking energy applied over the distance. The distance d in equation 2 may be evaluated over a future route or alternatively can be at a point in time. When evaluating equation 2 at a point in time, the use of current and historical data may be used. For example, E kinetic  may be based on current vehicle speed, E grade  may be based on current vehicle angle of inclination, while both and E regen  and E friction  may be based on historical data such as vehicle and ambient temperature, and a duration the vehicle is currently operating, and historical drive cycle data including road grade, vehicle kinetic energy, battery power, accessory load profiles, driver deceleration rates, and route patterns. 
     Also, at each point in time, a parasitic loss force, F loss,parasitic  may be expressed as shown in equation 3 
     
       
         
           
             
               
                 
                   
                     F 
                     
                       loss 
                       , 
                       parasitic 
                       , 
                       i 
                     
                   
                   = 
                   
                     
                       
                         
                           0.5 
                            
                           
                             mv 
                             i 
                             2 
                           
                         
                         - 
                         
                           ( 
                           
                             
                               E 
                               
                                 regen 
                                 , 
                                 i 
                               
                             
                             + 
                             
                               E 
                               
                                 friction 
                                 , 
                                 i 
                               
                             
                           
                           ) 
                         
                       
                       
                         d 
                         i 
                       
                     
                     - 
                     
                       mg 
                        
                       
                           
                       
                        
                       sin 
                        
                       
                           
                       
                        
                       
                         θ 
                         i 
                       
                     
                   
                 
               
               
                 
                   ( 
                   3 
                   ) 
                 
               
             
           
         
       
     
     in which F loss,parasitic,i  is a road load force, v i  is vehicle mass, v i  is a velocity of the vehicle, d i  is a distance traveled over a duration, mg sin θ is an energy applied to the vehicle due to an angle of inclination evaluated over the distance and (E regen +E friction )/d i  is regenerative energy over the distance and a friction braking energy applied over the distance. The F loss,parasitic  changes dynamically as the vehicle is operated. Also, F loss,parasitic,i  can be aggregated and analyzed by a vehicle controller to obtain a function describing a speed-dependent parasitic force. The function obtained may be based on multiple methods including but not limited to regression analysis, linear interpolation, curve fitting, etc. 
     The driveline loss changes based on temperature changes along with other factors including changes in road surface, tire pressure and steering angle. In block  604 , available regenerative energy is calculated based on current and future data along with the road load force calculated in block  602 . An example equation to calculate available regenerative energy for a given time period and road grade is shown in equation 4 
         E   regen   =m∫v ( dv )− mg∫v  sin θ( dt )− F   loss,parasitic   ∫v ( dt )−∫ F   friction   v ( dt )   (4)
 
     in which E regen  is the anticipated or predicted regenerative energy, m f v(dv) is the kinetic energy based on vehicle speed and vehicle mass, mg∫v sin θ(dt) is the force over a distance associated with the angle of inclination and the mass of the vehicle, F loss,parasitic ∫v(dt) is the speed dependent parasitic loss or drivetrain loss over a distance based upon recent calculated road load losses or drivetrain losses, and ∫F friction v(dt) is an anticipated energy loss based on friction braking An estimated change in battery SOC is determined based on E regen  from equation 2 in block  606 . In block  608 , the estimated change in battery SOC is compared with a maximum battery SOC minus the current battery SOC. If the estimated change in battery SOC is greater than a maximum battery SOC minus the current battery SOC, then a target SOC or current flow limit is adjusted in block  610 . The adjustment of the target SOC may be a decrease of the target SOC such that current flows from the battery to reduce the battery SOC. This reduction in battery SOC makes capacity available in the battery for the anticipated regenerative braking energy. If the target SOC is not reduced, the available regenerative energy would not be captured in the battery system. 
       FIG. 7  is an exemplary graph  700  showing the recommended discharge power used by the vehicle controller to decrease battery SOC based on current SOC and the anticipated energy capture during the anticipated regenerative braking event. For example,  708  shows that when battery SOC is high and the anticipated regenerative energy is also high, the vehicle controller should reduce SOC via discharge power. The discharge can be performed using EV propulsion or auxiliary electrical loads. 
     Similar to the speed-based method described in  FIGS. 6-7 ,  FIG. 8  is an exemplary flow diagram  800  illustrating a method of modifying battery management at high SOC, in relation to a road grade, in order to ensure enough battery capacity to maximize energy capture during an imminent regenerative braking event. The diagram shows a grade-based target SOC computation for vehicle operation. In block  802  a location is determined using a computing system including a global positioning system. Along with the location, a route may be generated by the computing system or navigation system. The computing system may include elevation data such as topographical data for the route. But, due to changes in roadways and a possibility that the maps and topographical data may not be always accurate, the computer system may also utilize other sources including GPS data or data from sensors in other vehicle systems including a wheel speed sensor, a steering angle sensor and an atmospheric pressure sensor (MAP sensor) to determine elevation data. Also, data may include future data such as estimated duration of vehicle operation based on electricity only and road grade. Here the road grade may be based on the angle of inclination further determined by multiple means including an output of an inclinometer or a combination of a wheel speed sensor output indicative of vehicle acceleration along a longitudinal plane of the vehicle and a vehicle longitudinal accelerometer output indicative of an acceleration along the longitudinal plane as affected by gravity. In block  804 , a probable trajectory is calculated. In block  806 , assessment of the road grade along the current path is performed. This assessment may use topological data associated with the route or, alternatively, an output of a longitudinal accelerometer compared to a change in velocity based on an output from a wheel speed sensor may be used. 
     A potential or available regenerative energy is calculated in block  808 . The vehicle speed and road load is determined in blocks  810  and  812 . The required braking force and motor regenerative energy is determined in blocks  814  and  816 . Based on factors including vehicle speed, road load, required braking force and motor regenerative energy, available regenerative energy is calculated in block  818 . Based on the available regenerative energy, a corresponding change in SOC is calculated in block  820 . The target battery SOC operating range or setpoint is adjusted in block  822 . In block  824 , the controller discharges the battery by either keeping the engine shut-down longer while in EV-mode in order to use more battery energy for EV operation, or by reducing the engine output power and/or duration if the engine is running in order to use more battery energy for combined (hybrid) operation. In block  826 , the actual regenerative energy is compared to the expected regenerative energy, and the request is modified if appropriate. For example, if the engine is running but the controller has reduced its output based on anticipated regenerative energy, the engine output can be increased if the regenerative energy collected is less than expected, or decreased further if the regenerative energy collected is more than expected. Similarly, if the vehicle is in EV-mode because the controller was trying to deplete the battery faster to accommodate the expected regenerative energy collection, but the regenerative energy is less than expected, then the controller may choose to start the engine to augment battery charging or supplement electrical loads. 
       FIG. 9A  is an exemplary graph  900  that illustrates vehicle elevation  902 , a battery state of charge  904 , and internal combustion engine operation  906  in relation to time. At a point in time  910 , the internal combustion engine (ICE) is operating to provide power to propel the vehicle on a flat road at a velocity and maintain the traction battery at a battery state of charge (SOC). When the vehicle traverses a downhill slope, energy from the powertrain is converted to electricity and flows to the traction battery increasing the battery SOC. At a point in time  912 , the battery SOC crosses a stop engine threshold that triggers the engine to shut-off. The battery SOC may continue to increase because of current from the powertrain attributed to regenerative braking However once the battery SOC reaches a maximum operational SOC, additional energy available from braking while traversing the downhill grade  914  will not be stored in the battery. In this exemplary graph, element  902  is illustrating vehicle elevation, but element  902  may be used to illustrate vehicle speed, or a combination of vehicle speed and elevation. An alternative way to view element  902  is a change in energy state of the vehicle, such as changes in vehicle kinetic energy or vehicle potential. 
       FIG. 9B  is an exemplary graph  920  that illustrates vehicle elevation  922 , a battery state of charge  924 , and internal combustion engine operation  926  in relation to time. At a point in time  930 , the internal combustion engine (ICE) is operating to provide power to propel the vehicle on a flat road at a velocity and maintain the traction battery at a battery state of charge (SOC). As an alternative to  FIG. 9A , a vehicle or battery management system may reduce the target battery SOC such that potential regenerative energy may be captured. Here, the potential regenerative energy is expressed in equation 3 with current kinetic energy and current potential energy. The current kinetic energy is based on vehicle speed and vehicle mass, and the current potential energy is based on the road grade being associated with the angle of inclination. The potential regenerative energy is also based on the powertrain losses as determined by historical data. The result would be that a target SOC, or in an alternative an engine shut-off threshold SOC, may be reduced by the potential regenerative energy. Further, historical drive cycle data including historical driver braking, historical deceleration rates, historical auxiliary load usage, battery life, or the efficiency of converting kinetic and potential energy to electric energy may be used to adjust the potential regenerative energy. In this exemplary graph, element  922  is illustrating vehicle elevation, but element  922  may be used to illustrate vehicle speed, or a combination of vehicle speed and elevation. An alternative way to view element  922  is a change in energy state of the vehicle, such as changes in vehicle kinetic energy or vehicle potential. 
     If future information is known, such as a future route based on topographical information, future changes in elevation, future auxiliary load usage, or a future recharge event, the potential regenerative energy calculation may include this information. The knowledge of a future speed and a future road grade along a future route allows a predicted kinetic energy and predicted potential energy to be determined. For example, an engine normally shut off at point  928  may be shut off at point  932  based on knowledge of a future downhill slope  934 . This may be due to a reduction in the engine stop threshold. Once the engine is turned off at  932 , the vehicle is then operated by electricity only and the battery SOC decreases due to the current flowing from the battery to the vehicle. The decrease in SOC is shown by element  936 . When the vehicle traverses the downhill slope  934 , the energy from regenerative braking allows the vehicle to flow a current to the battery thus increasing the battery SOC  938 . Also, based on historical driver braking or historical deceleration rates, the efficiency of converting kinetic and potential energy to electric energy may be used to adjust the potential regenerative energy. It may be beneficial to adjust the vehicle speed in relation to the slope. For example on a steep incline, it may be beneficial to reduce the vehicle speed. However in a vehicle with a cruise control module or an adaptive cruise control module, or based on customer feedback, operation at a constant velocity may provide a better driving experience for the operator and passengers. As such, the vehicle may be required to adjust for constant velocity operation or in the case of an adaptive cruise control module, a separation distance with the tracking vehicle may be adjusted in anticipation of changes in a speed of the tracking vehicle. 
     The processes, methods, or algorithms disclosed herein can be deliverable to/implemented by a processing device, controller, or computer, which can include any existing programmable electronic control unit or dedicated electronic control unit. Similarly, the processes, methods, or algorithms can be stored as data and instructions executable by a controller or computer in many forms including, but not limited to, information permanently stored on non-writable storage media such as ROM devices and information alterably stored on writeable storage media such as floppy disks, magnetic tapes, CDs, RAM devices, and other magnetic and optical media. The processes, methods, or algorithms can also be implemented in a software executable object. Alternatively, the processes, methods, or algorithms can be embodied in whole or in part using suitable hardware components, such as Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), state machines, controllers or other hardware components or devices, or a combination of hardware, software and firmware components. 
     While exemplary embodiments are described above, it is not intended that these embodiments describe all possible forms encompassed by the claims. The words used in the specification are words of description rather than limitation, and it is understood that various changes can be made without departing from the spirit and scope of the disclosure. As previously described, the features of various embodiments can be combined to form further embodiments of the invention that may not be explicitly described or illustrated. While various embodiments could have been described as providing advantages or being preferred over other embodiments or prior art implementations with respect to one or more desired characteristics, those of ordinary skill in the art recognize that one or more features or characteristics can be compromised to achieve desired overall system attributes, which depend on the specific application and implementation. These attributes may include, but are not limited to cost, strength, durability, life cycle cost, marketability, appearance, packaging, size, serviceability, weight, manufacturability, ease of assembly, etc. As such, embodiments described as less desirable than other embodiments or prior art implementations with respect to one or more characteristics are not outside the scope of the disclosure and can be desirable for particular applications.