Abstract:
A vehicle and method for controlling the vehicle includes identifying an EV-priority zone for the vehicle along a trip path, determining the position of the vehicle with respect to the expected upcoming EV-priority zone; implementing an electric-only mode of operation of the vehicle based on the position of the vehicle and a current operating mode of the vehicle; and implementing a charging mode of operation of the vehicle based on the position of the vehicle and a current operating mode of the vehicle.

Description:
TECHNICAL FIELD 
       [0001]    The disclosure relates to a method of control for a vehicle such as a hybrid or a plug-in hybrid electric vehicle. 
       BACKGROUND 
       [0002]    Hybrid Electric Vehicles (HEVs) typically have power supplied by a battery powered electric motor, an engine, or a combination thereof. Some HEVs have a plug-in feature which allows the battery to be connected to an external power source for recharging, and are called Plug-in HEVs (PHEVs). Electric-only mode (EV mode) in HEVs and PHEVs allows the vehicle to operate using the electric motor alone, while not using the engine. Operation in EV mode may enhance the ride comfort by providing lower noise and better driveability of the vehicle, e.g., smoother electric operation, lower noise, vibration, and harshness (NVH), and faster vehicle response. Operation in EV mode also benefits the environment with zero emissions from the vehicle during this period of operation. 
       SUMMARY 
       [0003]    Various embodiments provide an intelligent way to automatically prioritize the EV operation in EV-desirable areas and encourage the edited vehicle to stay in EV mode for longer than it would under normal operation. 
         [0004]    In one embodiment, a method to control a powertrain for a vehicle having electric motor and engine propulsion devices is provided. The method identifies an EV-priority zone for the vehicle along a trip path, determines the position of the vehicle with respect to the expected upcoming EV-priority zone, implements an electric-only mode of operation of the vehicle based on the position of the vehicle and a current operating mode of the vehicle, and implements a charging mode of operation of the vehicle based on the position of the vehicle and a current operating mode of the vehicle. 
         [0005]    In another embodiment, a method to control a powertrain for a vehicle having electric motor and engine propulsion devices is provided. The method provides a recommendation for an EV-priority segment along a trip path using at least one of a current driving pattern, a future driving pattern, and geographic information. The current and future driving patterns are provided by a database of possible driving patterns. An electric-only mode of operation of the vehicle is implemented to delay an engine-on command when the vehicle is within the EV-priority segment with a state of charge of a battery above a minimum threshold. A charging mode of operation of the vehicle is also implemented to increase a power output of the engine thereby increasing the state of charge of the battery when the vehicle is approaching the EV-priority segment and the engine is on. 
         [0006]    In yet another embodiment, a vehicle is provided with an electric motor, a battery coupled to the electric motor, an engine, and a controller. The electric motor and the engine are coupled to wheels of the vehicle via a transmission. The controller is electronically coupled to the electric motor, the battery, and the engine. The controller is configured to: (i) determine an electric priority segment along a trip path and determine the position of the vehicle along the trip path, (ii) implement an electric-only mode of operation of the vehicle to delay an engine-on command when the vehicle is within an EV-priority segment with a state of charge of a battery above a minimum threshold, and (iii) implement a charging mode of operation of the vehicle to increase power output of the engine, thereby increasing state of charge of the battery when the vehicle is approaching the EV-priority segment and the engine is on. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0007]      FIG. 1  is a schematic representation of a hybrid electric vehicle powertrain capable of embodying the invention; 
           [0008]      FIG. 2  is a diagram of the power flow paths for the components of the powertrain shown in  FIG. 1 ; 
           [0009]      FIG. 3  is a schematic of an algorithm to determine the EV-priority zones according to an embodiment; 
           [0010]      FIG. 4  is a schematic depicting zones along a trip and the associated modes of vehicle operation in the respective zones according to embodiment; 
           [0011]      FIG. 5  is a schematic of an algorithm to prioritize an EV mode according to an embodiment; 
           [0012]      FIG. 6  is a schematic of an algorithm to prioritize battery usage according to an embodiment; and 
           [0013]      FIG. 7  is a schematic of an algorithm to control state of charge of a battery before an expected upcoming EV-priority zone according to an embodiment. 
       
    
    
     DETAILED DESCRIPTION 
       [0014]    As required, detailed embodiments of the present invention are disclosed herein; however, it is to be understood that the disclosed embodiments are merely exemplary of the invention that may be embodied in various and alternative forms. The figures are not necessarily to scale; some features may 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. 
         [0015]    Vehicles may have two or more propulsion devices, such as a first propulsion device and a second propulsion device. For example, the vehicle may have an engine and an electric motor, a fuel cell and an electric motor, or other combinations of propulsion devices as are known in the art. The engine may be a compression or spark ignition internal combustion engine, or an external combustion engine, and the use of various fuels is contemplated. In one example, the vehicle is a hybrid vehicle (HEV), and additionally may have the ability to connect to an external electric grid, such as in a plug-in electric hybrid vehicle (PHEV). The PHEV structure is used in the figures and to describe the various embodiments below; however, it is contemplated that the various embodiments may be used with vehicles having other propulsion devices or combinations of propulsion devices as is known in the art. 
         [0016]    A plug-in Hybrid Electric Vehicle (PHEV) involves an extension of existing Hybrid Electric Vehicle (HEV) technology, in which an internal combustion engine is supplemented by an electric battery pack and at least one electric machine to further gain increased mileage and reduced vehicle emissions. A PHEV uses a larger capacity battery pack than a standard hybrid vehicle, and it adds a capability to recharge the battery from an electric power grid, which supplies energy to an electrical outlet at a charging station. This further improves the overall vehicle system operating efficiency in an electric driving mode and in a hydrocarbon/electric blended driving mode. 
         [0017]    Conventional HEVs buffer fuel energy and recover kinematic energy in electric form to achieve the overall vehicle system operating efficiency. Hydrocarbon fuel is the principal energy source. For PHEVs, an additional source of energy is the amount of electric energy stored in the battery from the grid after each battery charge event. 
         [0018]    While most conventional HEVs are operated to maintain the battery state of charge (SOC) around a constant level, PHEVs use as much pre-saved battery electric (grid) energy as possible before the next battery charge event. The relatively low cost grid supplied electric energy is expected to be fully utilized for propulsion and other vehicle functions after each charge. After the battery SOC decreases to a low conservative level during a charge depleting event, the PHEV resumes operation as a conventional HEV in a so-called charge sustaining mode until the battery is re-charged. 
         [0019]      FIG. 1  illustrates an HEV  10  powertrain configuration and control system. A power split hybrid electric vehicle  10  may be a parallel hybrid electric vehicle. The HEV configuration as shown is for example purposes only and is not intended to be limiting as the present disclosure applies to HEVs and PHEVs of any suitable architecture. 
         [0020]    In this powertrain configuration, there are two power sources  12 ,  14  that are connected to the driveline:  12 ) a combination of engine and generator subsystems using a planetary gear set to connect to each other, and  14 ) the electric drive system (motor, generator, and battery subsystems). The battery subsystem is an energy storage system for the generator and the motor. 
         [0021]    The changing generator speed will vary the engine output power split between an electrical path and a mechanical path. In addition, the control of engine speed results in a generator torque to react against the engine output torque. It is this generator reaction torque that conveys the engine output torque to the ring gear of the planetary gear set  22 , and eventually to the wheels  24 . This mode of operation is called “positive split”. It is noted that because of the kinematic properties of the planetary gear set  22 , the generator  18  can possibly rotate in the same direction of its torque that reacts against the engine output torque. In this instance, the generator  18  inputs power (like the engine) to the planetary gear set to drive the vehicle  10 . This operation mode is called “negative split”. 
         [0022]    As in the case of the positive split mode, the generator torque resulting from the generator speed control during a negative split reacts to the engine output torque and conveys the engine output torque to the wheels  24 . This combination of the generator  18 , the motor  20  and the planetary gear set  22  is analogous to an electro-mechanical CVT. When the generator brake (shown in  FIG. 1 ) is actuated (parallel mode operation), the sun gear is locked from rotating and the generator braking torque provides reaction torque to the engine output torque. In this mode of operation, all the engine output power is transmitted, with a fixed gear ratio, to the drivetrain through the mechanical path. 
         [0023]    In a vehicle  10  with a power split powertrain system, unlike conventional vehicles, the engine  16  requires either the generator torque resulting from engine speed control or the generator brake torque to transmit its output power through both the electrical and mechanical paths (split modes) or through the all-mechanical path (parallel mode) to the drivetrain for forward motion. 
         [0024]    During operation using the second power source  14 , the electric motor  20  draws power from the battery  26  and provides propulsion independently of the engine  16  for forward and reverse motions. This operating mode is called “electric drive” or electric-only mode or EV mode. In addition, the generator  18  can draw power from the battery  26  and drive against a one-way clutch coupling on the engine output shaft to propel the vehicle  10  forward. The generator  18  alone can propel the vehicle  10  forward when necessary. This mode of operation is called generator drive mode. 
         [0025]    The operation of this power split powertrain system, unlike conventional powertrain systems, integrates the two power sources  12 ,  14  to work together seamlessly to meet the driver&#39;s demand without exceeding the system&#39;s limits (such as battery limits) while optimizing the total powertrain system efficiency and performance. Coordination control between the two power sources is needed. As shown in  FIG. 1 , there is a hierarchical vehicle system controller (VSC)  28  that performs the coordination control in this power split powertrain system. Under normal powertrain conditions (no subsystems/components faulted), the VSC interprets the driver&#39;s demands (e.g. PRND and acceleration or deceleration demand), and then determines the wheel torque command based on the driver demand and powertrain limits. In addition, the VSC  28  determines when and how much torque each power source needs to provide in order to meet the driver&#39;s torque demand and to achieve the operating point (torque and speed) of the engine. 
         [0026]    The battery  26  is additionally rechargeable in a PHEV vehicle  10  configuration (shown in phantom), using a receptacle  32  which is connected to the power grid or other outside electrical power source and is coupled to battery  26 , possibly through a battery charger/converter  30 . 
         [0027]    The vehicle  10  may be operated in electric mode (EV mode), where the battery  26  provides all of the power to the electric motor  20  to operate the vehicle  10 . In addition to the benefit of saving fuel, operation in EV mode may enhance the ride comfort through lower noise and better driveability, e.g., smoother electric operation, lower noise, vibration, and harshness (NVH), and faster response. Operation in EV mode also benefits the environment with zero emissions from the vehicle during this mode. 
         [0028]    Regions or sections of roadway may be defined as EV-priority zones, or the driving area where operation of the vehicle  10  in EV mode has benefits as mentioned above. EV-priority zones include city driving zones in an urban area with frequent stops or congested traffic, specific trip segments and geographic regions that have strict emission regulations, etc. Within the EV-priority zones, the vehicle may be operated in EV mode, assuming the vehicle  10  has sufficient battery  26  charge, etc. 
         [0029]    The VSC  28  is adapted to recognize EV-priority zones using a driving pattern identification method. The driving pattern identification method uses an algorithm that detects and recognizes real-world driving conditions as one of a set of standard drive patterns, including for example, city, highway, urban, traffic, low emissions, etc. In one embodiment, the algorithm is based on machine learning using a neural network. In other embodiments, the algorithm is based on support vector machines, fuzzy logic, or the like. 
         [0030]    Regarding the existing driving pattern identification method, it is known that fuel efficiency is connected to individual driving styles, roadway types, and traffic congestion levels. A set of standard drive patterns, called facility-specific cycles, have been developed to represent passenger car and light truck operations over a broad range of facilities and congestion levels in urban areas. (See, for instance, Sierra Research, 30 ‘SCF Improvement—Cycle Development’, Sierra Report No. SR2003-06-02 (2003).) Driving styles have been captured in these standard drive patterns as well. For example, for the same roadway type and traffic level, different drivers may lead to different drive patterns. An online driving pattern identification method that automatically detects real-world driving condition and driving style and recognizes it as one of the standard patterns has been developed. (See, for example, Jungme Park, ZhiHang Chen, Leonidas Kiliaris, Ming Kuang, AbulMasrur, Anthony Phillips, Yi L. Murphey, ‘Intelligent Vehicle Power Control based on Machine Learning of Optimal Control Parameters and Prediction of Road Type and Traffic Congestions’, IEEE Transactions on Vehicular Technology, 17 July 2009, Volume 58, Issue 9.) This online driving pattern method is based on machine learning using a neural network and its accuracy has been proven by simulations. 
         [0031]    It should be noted that the standard drive patterns that are to be considered for use during EV operation mode may be customized during the feature selection process by varying features including: average vehicle speed, maximum speed average vehicle acceleration, maximum acceleration, number of stops, stopping time, etc. Therefore, the EV-priority zones can be configured and calibrated to fit various customer preferences or profiles. 
         [0032]      FIG. 3  illustrates the algorithm flow  50  for arbitration and identification of EV-priority zones by the VSC  28 . The algorithm  50  collects information through various processes, including: current driving pattern  52 , predicted future driving patterns  54 , and geographic information  56 . 
         [0033]    The current driving pattern determination process  52  determines the current driving pattern  58  of the vehicle. The current driving pattern  58  may be derived from the vehicle states and driving condition of an immediately recent time frame, such as (t-T, t) where t is the current time and T is a selected time preset. The VSC  28  provides vehicle state information  60 , such as engine state, battery state, and the like, to a signal processor  62 . The signal processor  62  uses the vehicle state information  60  to determine processed data  64 , such as vehicle speed, grade profile, etc. Various selected data  66 , or pattern parameters, are extracted from the processed data  64  using a pattern parameter extraction function  68 . The pattern parameters  66  are provided as an input to a pattern recognition algorithm  70  which recognizes the current driving pattern  58  from the pattern parameters  66 . The pattern recognition algorithm  70  is a driving pattern identification method as described previously. 
         [0034]    The predicted future driving patterns process  54  determines one or more predicted future driving patterns  72  of the vehicle along a trip path. The predicted future driving patterns  72  may be derived from various predictive information sources  74 , such as signals and data from an on-board navigation system with global positioning, a vehicle to vehicle system (V2V), a vehicle to roadside infrastructure system (V2I), a cellular network, or the like. The sources  74  provide route information  76  to the VSC  28  such as predicted vehicle speeds, predicted road conditions, distances, and the like. A traffic module may be provided to additionally provide predicted traffic information  80  and supplement the route related information  76 . Pattern parameters  82  are extracted from the predictive information  78 ,  80  using a pattern parameter extraction function  84 . The pattern parameters  82  are provided as inputs to a pattern recognition algorithm  86  which recognizes the predicted driving pattern  72 . The pattern recognition algorithm  86  is a driving pattern identification method as described previously. The algorithm  54  labels each future driving pattern as one of the pre-defined driving patterns and then divides the trip into multiple segments of pre-defined driving patterns. 
         [0035]    The geographic information process  56  uses a geographic recognition algorithm  90  to determine geographic information of the trip  88  using data from predictive information sources  74 , such as signals and data from an on-board navigation system with global positioning, or the like. The geographic information process  56  may be configured to identify if the current location of the vehicle  10  is within an EV-priority zone (e.g., in an urban area or in a region with strict emission regulations) or in an open zone where there is no preference as to vehicle operation. 
         [0036]    An arbitration process  92  receives the current driving pattern  58 , predicted future driving patterns  72 , and geographic information  88  to determine the EV-priority zones  94  for the vehicle  10  at its present state and/or at various positions along a trip. 
         [0037]    An example of EV-priority zones  94  as determined by the arbitration process  92  are illustrated in  FIG. 4 . The trip  100  is labeled into different segments  102  by the arbitration process  92 . The trip  100  is divided into EV-priority zones  104 , which favor operation of the vehicle in EV mode, and open zones  106 , where there is no preference for the vehicle operation, e.g. EV mode, hybrid mode, etc. 
         [0038]    A mode selection algorithm  110 , as illustrated in  FIG. 5 , is used to activate either an EV-priority operation mode  112  using an EV-priority algorithm  113 , or an SOC preserving/charging mode  114  using an SOC preserving/charging algorithm  115 . For example, the EV priority operation mode  112  causes the vehicle to operate using battery power, and delay engine operation. The state of charge (SOC) preserving/charging mode  114  causes the vehicle to store or retain additional electrical energy in the battery, while the engine is operating. 
         [0039]    The modes  112 ,  114  may be scheduled to correspond with various trip zones  102 . For example, the EV priority operation mode  112  is predictively scheduled to operate when the vehicle is in an EV-priority zone  104  based on the algorithm  113 . The SOC preserving/charging mode  114  is predictively scheduled to operate when the vehicle is in an open zone  106  prior to entering an EV-priority zone  104 , based on the algorithm  115 . 
         [0040]    For the mode selection process  100 , the algorithm  110  determines if the vehicle is currently in an EV-priority zone  106  at step  116 . If the vehicle is in an EV-priority zone  106 , the algorithm  110  runs the EV priority algorithm  113  to prioritize battery usage to delay operation of the engine and operate the vehicle in mode  112 . If the vehicle is not in an EV-priority zone  104 , the algorithm  110  proceeds to step  118 , which determines if the vehicle is approaching an EV-priority zone  104 , and may call algorithm  115 . If the vehicle is approaching an EV-priority zone  104 , for example, within a specified distance or travel time of the zone  104 , the algorithm  110  runs the SOC charging/preserving algorithm  115  to activate the SOC preserving/charging mode  114  to conserve or add additional electric energy to the battery to prepare for the expected upcoming EV-priority zone  104  and EV operation. If the vehicle  10  is not approaching an EV-priority zone  104  at step  118 , the algorithm  100  causes the vehicle to continue operation under its current or default strategy  120 . The default strategy  120  may be electric and/or engine operation based on the operating conditions of the vehicle  10  as determined using the VSC  28 . 
         [0041]    In various embodiments, the algorithm  110  may be overridden due to other priority events where the vehicle  10  is required to operate in an EV mode, engine mode, or a combination thereof. For example, a priority event may be a high-priority engine ON/OFF command, caused by temperature constraints, battery discharge limits, battery over-voltage protection, engine cold start, and the like. 
         [0042]      FIG. 6  illustrates an embodiment of the algorithm  113  to determine operation in an EV priority mode  112  by prioritizing the battery usage to delay engine operation in the vehicle  10 . The algorithm  122  receives the battery discharge limits  124  and the electric motor power limits  126 . The algorithm  122  compares the limits  124 ,  126  at step  128  to determine the electrical discharge limit  130 . An arbitration process  132  determines if the vehicle  10  is capable of running in electric only operation by comparing the electric discharge limit  130  to the requested driver power  134 . The arbitration process  132  also determines if the SOC of the battery  136  is above the minimum threshold state of charge. If the current electrical limit  130  is high enough to operate the electric motor to meet the driver power command  134 , and the SOC  136  is above the minimum threshold, the vehicle is capable of operation in EV mode and the process  122  sets the default power-based engine pull-up pull-down (EPUD) command to zero at step  138 , which causes the vehicle  10  to operate in EV mode  112  if no other conditions trigger a higher priority engine ON command. 
         [0043]      FIG. 7  illustrates an embodiment of the algorithm  115  which determines preserving/charging the SOC  114 . The algorithm  115  is activated if the vehicle is approaching an EV-priority zone  104 , as determined by step  118 , and when the engine is operating as determined by step  140 . The algorithm  115  receives the SOC of the battery  142 , and time or distance information  144  to the next EV-priority zone. Based on a calibration table  146 , or other function, the algorithm  115  increases the engine power output by making a power adjustment  148 . The additional engine power  148  for charging battery may be scheduled as a function of the SOC, and the remaining time or distance to the next EV-priority zone  104 . The power adjustment  148  is set at zero for normal operation. The power adjustment  148  acts to increase the engine power compared to what it would normally produce under the present operating condition to provide excess power to charge the battery. The algorithm  115  operates when the engine is already operating to provide opportunistic charging of the battery. In some embodiments, the algorithm  115  will not pull the engine to operate if it is not running at that point. 
         [0044]    The flowchart  50  represents control logic which may be implemented by the VSC  28 , or another controller within the vehicle  10 , using hardware, software, or combination of hardware and software. For example, the various functions may be performed using a programmed microprocessor. The control logic may be implemented using any of a number of known programming or processing techniques or strategies and is not limited to the order or sequence illustrated. For instance, interrupt or event-driven processing is employed in real-time control applications, rather than a purely sequential strategy as illustrated. Likewise, parallel processing, multitasking, or multi-threaded systems and methods may be used. 
         [0045]    The methods and algorithms are independent of any particular programming language, operating system processor, or circuitry used to develop and/or implement the control logic illustrated. Likewise, depending upon the particular programming language and processing strategy, various functions may be performed in the sequence illustrated at substantially the same time or in a different sequence. The illustrated functions may be modified or in some cases omitted without departing from the spirit or scope of the present invention. 
         [0046]    While exemplary embodiments are described above, it is not intended that these embodiments describe all possible forms of the invention. Rather, the words used in the specification are words of description rather than limitation, and it is understood that various changes may be made without departing from the spirit and scope of the invention. Additionally, the features of various implementing embodiments may be combined to form further embodiments of the invention.