JP4571917B2 - Control device for hybrid vehicle - Google Patents

Description

  The present invention relates to a control device for a hybrid vehicle.

Recently, various hybrid vehicles have been proposed that include an internal combustion engine and an electric motor and drive with wheels driven by any of them, and the technology described in Patent Document 1 can be given as an example. In this technology, when the vehicle speed is low and the accelerator opening is small, the electric motor is used. When the vehicle speed is high, the internal combustion engine is used. When the vehicle speed is high and the accelerator opening is large, both the internal combustion engine and the electric motor are used. At the same time, when an abnormality is detected in the motor drive device such as a high motor temperature, the traveling region of the internal combustion engine is configured to be expanded to the low speed side.
JP-A-6-80048

  In the above-described conventional technology, the travel region is determined according to the vehicle speed and the accelerator opening, and the hysteresis is provided so that control hunting does not occur at the time of switching. It was not determined which way to drive in consideration of performance.

  Accordingly, an object of the present invention is to eliminate the above-described problems, and a hybrid vehicle control device that improves fuel efficiency and drivability in a hybrid vehicle that can run on at least one of an internal combustion engine and an electric motor. Is to provide.

In order to achieve the above object, in claim 1, the engine includes an internal combustion engine, an electric motor, and power storage means for supplying electric power to the electric motor while storing electric power generated by the electric motor, In a hybrid vehicle that travels by driving wheels with at least one of the internal combustion engine and the electric motor, a required driving force calculating means that calculates a required driving force required by the vehicle from a vehicle speed and an accelerator opening, and the electric motor from the vehicle speed. It calculates the maximum driving force that can be output, motor load factor calculating means for calculating a motor load factor indicating a ratio occupied by the required driving force to the maximum driving force, which is set according to the vehicle speed for the motor load factor Fuel consumption is reduced by performing fuzzy inference from a membership function and traveling by the motor as compared to traveling by the internal combustion engine. Engine running fitness calculating means for calculating a traveling fitness by the internal combustion engine during the upper limit of the reduced area and the maximum driving force, subjected to the fuzzy inference from the membership functions set for the rate of change of the accelerator opening Accelerating intention estimating means for estimating the driver's intention to accelerate, traveling for calculating a required traveling value by performing fuzzy inference based on the estimated acceleration intention and the membership function set for the calculated traveling suitability The demand value calculating means and the travel selecting means for selecting either the travel by the internal combustion engine or the travel by the electric motor based on the calculated travel request value are provided.

In the hybrid vehicle control device according to claim 2, the travel selection unit selects one of travel by the internal combustion engine and travel by the electric motor based on an integral value of the calculated travel request value. It was configured as follows.

  In the hybrid vehicle control device according to claim 3, when the estimated intention to accelerate increases and travel by the internal combustion engine is selected, both travel by the internal combustion engine and travel by the electric motor are performed. It was comprised so that the permission means to permit would be provided.

  In the hybrid vehicle control apparatus according to claim 4, the traffic jam / high speed estimation means for estimating the traffic jam or the high speed by performing fuzzy inference from a membership function preset for the vehicle speed, and the estimated It is configured to include a remaining capacity target value changing means for changing the target value of the remaining capacity of the power storage means in accordance with traffic jam / high speed.

  In the hybrid vehicle control device according to claim 5, a gradient estimation value of a travel path is calculated from the vehicle speed and the required driving force, and fuzzy inference is performed from a membership function set in advance for the gradient estimation value. And a gradient degree estimating means for estimating the gradient degree of the traveling road, and a remaining capacity target value changing means for changing the target value of the remaining capacity of the power storage means according to the estimated gradient degree. .

  The hybrid vehicle control device according to claim 6 calculates a gradient estimation value of a travel path from the vehicle speed and the required driving force, and fuzzy inference from a membership function set in advance for the gradient estimation value. And a second fuzzy inference based on a membership function set with respect to the estimated gradient degree and the calculated driving fitness degree, and The vehicle is configured to include travel suitability correction means for correcting the travel suitability.

Ratio In the claim 1, and calculates a required driving force which the vehicle from the vehicle speed and the accelerator opening requires, to calculate the maximum driving force motor may be output from the vehicle speed, occupied by the required driving force to the maximum driving force The motor load factor is calculated, the fuzzy reasoning is performed from the membership function set according to the vehicle speed for the motor load factor, and the fuel consumption is reduced by running with the motor compared to running with the internal combustion engine. calculating a running fit by the internal combustion engine between the upper limit and the maximum driving force of performing fuzzy inference to estimate the acceleration intention of the driver from the membership functions set for the rate of change of the accelerator opening is estimated acceleration intention and based on the membership functions set for the calculated running fit calculates the travel request value by performing the fuzzy inference, calculator and Based on the travel request value, since as configured to select one of running by driving an electric motor by the internal combustion engine, it is possible to improve the fuel efficiency and drivability. In addition, when the accelerator opening changes suddenly, it is possible to quickly switch (select) to travel by the internal combustion engine, so that the driver does not feel insufficient output.

  That is, the fuel consumption reduction region where the fuel consumption (fuel consumption) is reduced by running with an electric motor as compared with running with an internal combustion engine is low vehicle speed or low load running during cruise, The output width is narrow, so the threshold value of the required driving force for traveling by the motor and traveling by the internal combustion engine is narrowed, and it becomes easy to cause hunting for switching between traveling and the original performance of the motor cannot be used up. . However, with the configuration as described above, when the required driving force corresponding to the maximum driving force of the electric motor is generated, it is possible to quickly switch to the driving by the internal combustion engine, while reliably selecting the driving by the electric motor in the fuel consumption reduction region. can do. When the required driving force exceeding the upper limit value of the fuel efficiency reduction region is generated, after the passage of time according to the degree of traveling suitability for the region, that is, when the required driving force is small, it can be traveled by the internal combustion engine in a short time. Can be switched. Furthermore, by calculating the running suitability between the upper limit value and the maximum driving force, not only the threshold for the required driving force, so-called play can be set and switching hunting can be prevented more reliably. Can do. Thus, drivability and fuel consumption can be improved by facilitating traveling by the electric motor in the fuel consumption reduction region.

In the hybrid vehicle control device according to the second aspect, the travel selection means is configured to select either the travel by the internal combustion engine or the travel by the electric motor based on the calculated travel request value . In addition to the effect, when the required driving force exceeding the upper limit value of the fuel efficiency reduction region occurs, the internal combustion is performed after a lapse of time according to the degree of driving suitability for the region, that is, for a long time if the required driving force is small, and for a short time if it is large It can be switched to running by an engine.

  In the hybrid vehicle control device according to claim 3, when the estimated intention to accelerate increases and the traveling by the internal combustion engine is selected, the permission for allowing both the traveling by the internal combustion engine and the traveling by the electric motor is permitted. Since it comprises so that a means may be provided, the effect similar to Claim 2 can be acquired.

  In the hybrid vehicle control device according to claim 4, fuzzy inference is performed from a membership function set in advance with respect to the vehicle speed to estimate a traffic jam or a high speed, and a power storage means is provided according to the estimated traffic jam / high speed. For example, by changing the lower limit of the target value according to traffic jams / high speeds, the usage range of the power storage means can be increased during traffic jams, and driving with an electric motor can be performed. This can improve fuel efficiency. In addition, at the time of high speed, it is possible to prepare for acceleration assistance at high speed by reducing the use width of the power storage means and maintaining a large remaining capacity.

  In the control apparatus for a hybrid vehicle according to claim 5, the gradient estimation value of the traveling road is calculated from the vehicle speed and the required driving force, and fuzzy inference is performed from a membership function set in advance for the gradient estimation value. Since the configuration is such that the gradient degree of the traveling road is estimated and the target value of the remaining capacity of the power storage means is changed according to the estimated gradient degree, in addition to the above-described effect, for example, if the vehicle is traveling uphill, the target value of the remaining capacity It is possible to positively assist the power by changing the lower limit of the power downward, and to improve the power performance when traveling on a mountain road or the like. For example, if the vehicle is traveling downhill, the upper limit of the target value is changed downward to reduce the frequency of power generation by the internal combustion engine, and energy recovery by deceleration regeneration can be efficiently realized.

  In the hybrid vehicle control device according to claim 6, the gradient degree of the traveling road is estimated by performing fuzzy inference from a membership function set in advance with respect to the gradient estimated value, and the estimated gradient degree is calculated. Since the second fuzzy inference is performed based on the membership function set for the travel suitability to correct the travel suitability, in addition to the above-described effects, for example, in downhill travel with a small required driving force, It is possible to improve driving performance by making it easy to select traveling and improving fuel efficiency, while in climbing traveling where the required driving force increases, it is easy to select traveling by an internal combustion engine and attach importance to power performance.

  The best mode for carrying out a hybrid vehicle control apparatus according to the present invention will be described below with reference to the accompanying drawings.

  FIG. 1 is a schematic diagram generally showing a control apparatus for a hybrid vehicle according to an embodiment of the present invention.

  Reference numeral 10 in FIG. 1 indicates a hybrid vehicle (hereinafter referred to as “vehicle”). The vehicle 10 includes an internal combustion engine (hereinafter referred to as “engine”, indicated as “ENG”) 12 and a transmission (shown as “T / M”) 14 for inputting the output of the engine 12. The transmission 14 shifts the output of the engine 12 and transmits it to the drive wheels (wheels) 16 to drive the vehicle 10.

  The engine 12 is a gasoline injection spark ignition type four-cylinder engine. Although not shown, the throttle valve in the engine 12 is controlled by a DBW system that is mechanically disconnected from the accelerator pedal and opened and closed by an actuator. . Specifically, the transmission 14 is an automatic transmission.

  A first electric motor (hereinafter referred to as “first motor”) 20 is directly connected to the engine 12. The first motor 20 is a DC brushless motor, more specifically, an AC synchronous motor. The first motor 20 always rotates when the engine 12 rotates, and is energized when the engine 12 is started to crank and start the engine 12. The first motor 20 assists the rotation of the engine 12 when energized, and generates electric power by converting the kinetic energy generated by the rotation of the crankshaft into electric energy when rotated by the engine 12 without being energized. Functions as a generator.

A second electric motor (hereinafter referred to as “second motor”) 26 is connected to the drive wheel 16 via a differential gear 22 and a clutch 24. The second motor 26 is also a DC brushless motor, more specifically, an AC synchronous motor. When the second motor 26 is energized and connected by the clutch 24, the drive wheel 16 is directly driven. The second motor 26 while being selectively driven with the engine 12, such as during acceleration rotate the assist (speed increasing) of being driven with the engine 1 2 engine 12. The second motor 26 also has a regenerative function that converts the kinetic energy generated by the rotation of the drive wheels 16 into electric energy and outputs it when connected by the clutch 24 when not energized.

  The first and second motors 20 and 26 are connected to a battery (shown as “BAT”) 34 through power drive units (shown as “PDU”) 30 and 32. Each of the PDUs 30 and 32 includes an inverter, converts the direct current supplied (discharged) from the battery 34 into alternating current and supplies the alternating current to the first and second motors 20 and 26. The alternating current generated or regenerated by the second motors 20 and 26 is converted into direct current and supplied to the battery 34 (the battery 34 is charged). The battery 34 is formed by connecting an appropriate number of nickel-metal hydride (Ni-MH) batteries in series.

  Thus, the hybrid vehicle 10 supplies power to the engine 12, the first and second motors 20, 26, and the first and second motors 20, 26, while the first and second motors 20, 26, In particular, a battery 34 that stores electric power generated by the first motor 20 is provided, and the vehicle travels by driving the wheels 16 by at least one of the engine 12 and the second motor 26.

  As illustrated, the vehicle 10 includes an engine control unit (hereinafter referred to as “ENG ECU”) 40 that controls the operation of the engine 12 and a motor control unit (hereinafter referred to as “MOT ECU”) that controls the operation of the first and second motors. ) 42, a charge state of the battery 34 is calculated by calculating a state of charge (SOC) of the battery 34, and a management control unit (referred to as “MG ECU”) 44 that controls the operation of the PDUs 30 and 32, A shift control unit (referred to as “T / M ECU”) 46 that controls the operation of the machine 14 is provided. An ECU (Electronic Control Unit) such as the ENG ECU 40 is composed of a microcomputer and is connected to each other via a signal line 50 so as to be able to communicate with each other.

  A current / voltage sensor 52 is disposed in the energization path between the battery 34 and the PDUs 30 and 32, and generates an output corresponding to the output terminal voltage of the battery 34 and the current discharged from the battery 34. An accelerator opening sensor 54 is disposed in the vicinity of an accelerator pedal (not shown) on the driver's seat floor (not shown) of the vehicle 10, and the accelerator pedal opening operated by the driver, that is, the accelerator pedal An output corresponding to the depression amount AP is generated. A vehicle speed sensor 56 is disposed in the vicinity of a drive shaft (not shown) of the vehicle 10 and generates an output corresponding to the vehicle speed V.

  The outputs of the sensors 52, 54, and 56 are input to the MG ECU 44. The MG ECU 44 calculates the state of charge SOC of the battery 34 from the output of the current / voltage sensor 52. Further, the MG ECU 44 inputs the current ratio (transmission ratio) Ratio of the transmission 14 from the T / M ECU 46.

  FIG. 2 is a block diagram showing the operation of the control device for the hybrid vehicle shown in FIG. The illustrated process is executed by the MG ECU 44.

  Outlined with reference to FIG. 2, in this apparatus, torque or driving force is calculated, and based on this, it is determined which of the engine 12 and the second motor 26 should run. That is, from the vehicle speed V and the current gear ratio Ratio, the illustrated characteristics set at the vehicle speed V for the acceleration G are retrieved in the calculation block 44a, and the engine 12 or the second motor 26 is determined based on the vehicle speed V and the gear ratio Ratio at that time. The maximum acceleration GMAX that can be generated by the vehicle 10 is calculated by the above, and the illustrated characteristic set by the coefficient K for the accelerator opening AP is searched in the calculation block 44b from the vehicle speed V and the accelerator opening AP. A ratio APS that can be generated at the current accelerator opening AP with respect to the vehicle speed V at that time is calculated.

  Next, the maximum acceleration GMAX and the ratio APS calculated in the multiplication stage 44c are multiplied, and the vehicle speed V, the gear ratio Ratio, and the accelerator opening AP at that time, in other words, generated at an arbitrary accelerator opening at a certain vehicle speed. The power acceleration G, that is, the required acceleration GCMD is calculated.

The calculated required acceleration GCMD is input to the vehicle body model 44d, where the required driving force FCMD is calculated according to the specifications of the vehicle 10 that are determined in advance. That is, in the vehicle body model 44d, the required driving force FCMD is calculated as follows according to the specifications of the vehicle 10 determined in advance based on the running resistance of the vehicle 10 and the required acceleration GCMD.
Required driving force FCMD = Air resistance + Rolling resistance-Required acceleration GCMD

  Next, the calculated required driving force FCMD is sent to the driving force switching point 44e and the fuzzy control unit 44f, and the fuzzy control unit 44f selects either the traveling by the engine 12 or the traveling by the second motor 26 (the driving force is Switched). That is, the fuzzy control unit 44f inputs the vehicle speed V, the state of charge SOC of the battery 34, and the accelerator pedal opening AP, and based on a request from the fuel consumption and power performance and a request from the capacity management (charge state SOC) of the battery 34. While traveling by the engine 12 or traveling by the second motor 26 is selected, the presence or absence of a power generation request is determined.

  When traveling by the engine 12 is selected, the required driving force to the engine 12 is corrected by the gear ratio, friction, etc. in the engine required torque calculation block 44g, and is set to the engine crank end torque command value ENGCMD, via the addition stage 44h. Output to the ENG ECU 40 that controls the operation of the engine 12. When traveling by the second motor 26 is selected, the required driving force to the second motor 26 is similarly calculated in the second motor required torque calculation block 44i, and the first and second motors are used as the motor shaft end torque command value MOTCMD. It is output to the MOT ECU 42 that controls the operations of the Nos. 20 and 26.

  The fuzzy control unit 44f also determines whether there is a power generation request as to whether the first motor 20 should generate power from the input value. When a power generation request is made, the power generation torque is calculated by the first motor request torque calculation block 44j, the calculated value is subtracted from the command value ENGCMD in the addition stage 44h, and the difference thus obtained is sent to the ENG ECU 40. All torques are calculated in units of [N · m].

  FIG. 3 is an explanatory diagram showing a travel region of the engine 12 and the second motor 26. In the figure, the horizontal axis represents the vehicle speed V, and the vertical axis represents the driving force. In addition, the symbol R / L in the figure indicates the running resistance on flat ground.

  In the hybrid vehicle 10 according to this embodiment, when an area in which fuel consumption is reduced by traveling by the second motor 26 as compared to traveling by the engine 12 is experimentally obtained, the region is as indicated by a symbol a. That is, since the second motor 26 (and the first motor 20) generates a large torque on the low rotation side due to the characteristics as a motor and most of the electric power required by the second motor 26 (and the first motor 20) is generated by the engine 12, the region a is This is a region where the vehicle speed V and load (driving force) are low. The characteristic indicated by symbol b indicates the upper limit value, and decreases as the vehicle speed V increases as shown. A region c where the load exceeds the upper limit value b is a region where the engine 12 should travel.

  In FIG. 3, when switching between traveling by the second motor 26 and traveling by the engine 12 with the upper limit value b as a boundary, the driving force at the switching point is uniquely determined with respect to the vehicle speed V. Is frequently used, resulting in switching hunting. The characteristic indicated by symbol d indicates the maximum motor driving force that can be output by the second motor 26, and is similarly obtained through experiments in advance. The maximum motor driving force also decreases as the vehicle speed V increases.

  For this reason, in this embodiment, a fuel consumption reduction region (region a) in which the traveling by the second motor 26 reduces the fuel consumption in accordance with the vehicle speed V rather than traveling by the engine 12 is obtained through experiments in advance. A membership function and a fuzzy rule set from the motor driving force, motor maximum driving force and running resistance required for running are configured. More specifically, the motor load factor is calculated from the required driving force FCMD in the current traveling state, and the motor load factor is smaller than the upper limit value b of the region a or larger than the motor maximum driving force (indicated by d). To determine the running fitness by the engine 12 for the region a, and integrate it. When the integral value is greater than or equal to a predetermined value, it is determined that traveling by the engine 12 is suitable, and when the integrated value is less than the predetermined value, traveling by the second motor 26 is suitable. This will be described later.

  FIG. 4 is a block diagram showing in detail the configuration of the fuzzy control unit 44f of FIG.

  As illustrated, the fuzzy control unit 44f includes an engine travel suitability estimation block 44f1, an acceleration intention estimation block 44f2, a gradient degree estimation block 44f3, a traffic jam / high speed estimation block 44f4, and an engine travel suitability estimation block 44f1. A motor / engine travel selection processing block that inputs the outputs of the acceleration intention estimation block 44f2 and the gradient degree estimation block 44f3 and outputs the travel degree of the engine 12 (in other words, the travel degree of the second motor 26). 44f5, an SOC management setting block 44f6 that inputs the output of the gradient degree estimation block 44f3 and the traffic jam / high speed estimation block 44f4 and outputs the presence / absence of a power generation request (in other words, the running degree of the engine 12).

  The outputs of the motor / engine running selection processing block 44f5 and the SOC management setting block 44f6 are both output as the engine running degree via the OR circuit 44f7, and either the running by the engine 12 or the running by the second motor 26 is selected. . Since the vehicle 10 according to this embodiment generates power with the first motor 20 when traveling with the engine 12, requesting power generation means requesting traveling with the engine 12, as described with reference to FIG. means.

  The output of the motor / engine travel selection processing block 44f5 is determined from the fuel consumption and power performance. The output of the SOC management setting block 44f6 is performed for the purpose of managing the capacity within the SOC management range corresponding to the preset vehicle speed. When the SOC is lower than the set value, the power generation request, that is, by the engine 12 is performed. The output is determined to require travel. When the SOC exceeds the set value, an upper limit SOC is set, and a power generation request is output so as to protect the battery 34 and prevent deterioration of fuel consumption due to excessive power generation. Further, based on the outputs of the gradient degree estimation block 44f3 and the traffic jam / high speed estimation block 44f4, it is determined whether or not the vehicle is traveling on an uphill / downhill road, a traffic jam road, or a highway, and the SOC management range is corrected. Therefore, optimal power generation management is performed according to the driving situation.

  FIG. 5 is an explanatory diagram showing details of the engine travel suitability estimation block 44f1.

  As shown in FIG. 6A, in the engine travel suitability estimation block 44f1, the maximum motor driving force that can be generated by the second motor 26 is calculated by searching the characteristic d shown in FIG. The Next, at block 44f12, the required driving force FCMD calculated by the vehicle body model 44d of FIG. 2 is divided by the calculated maximum motor driving force to calculate the motor load factor. The motor load factor means the load factor of the second motor 26 when the required driving force is borne by the maximum motor driving force.

  Next, in block 44f13, the calculated motor load factor and the vehicle speed V are input, and the engine running fitness is calculated from the illustrated membership function. FIG. 5B is an explanatory diagram showing the membership function and linguistic control rules. In FIG.5 (b), a horizontal axis shows a motor load factor.

  In the horizontal axis of the graph shown in FIG. 5 (b), b is the same as the upper limit value b (determined from the vehicle speed V) of the fuel consumption reduction region of FIG. 3, and the motor load factor is 1, and the motor load factor is the motor. Indicates that the maximum driving force has been reached. Based on the characteristics of FIG. 3, the linguistic control rule describes that the engine running fitness is small if the motor load factor is smaller than b, and the engine running fitness is large if the motor load factor is larger than 1. The Thus, in block 44f13, fuzzy inference is performed from the function and the rule, and a membership function indicating the engine running suitability is output.

  FIG. 6 is an explanatory diagram showing details of the acceleration intention estimation block 44f2.

  As shown in FIG. 5A, in the acceleration intention estimation block 44f2, the accelerator opening AP is input in the block 44f21, the differential value is calculated, and the value obtained through the low pass filter (LPF) is added to the accelerator opening AP. Thus, an accelerator opening estimated value AP_HAT is calculated. The calculated estimated value is sent to the block 44f22, where an acceleration intention, more precisely, an acceleration intention estimate is calculated from the illustrated membership function. FIG. 4B is an explanatory diagram showing the membership function and linguistic control rules. In FIG. 5B, the horizontal axis represents the acceleration intention estimated value. The values p and q are set as appropriate through experiments.

  The linguistic control rule is described as a small intention to accelerate if the estimated value AP_HAT is smaller than p, and a large intention to accelerate if the estimated value AP_HAT is larger than q. In block 44f22, fuzzy from these functions and rules. Inference is performed, and a membership function indicating an accelerated intention estimate is output.

  FIG. 7 is an explanatory diagram showing details of the gradient degree estimation block 44f3.

  As shown in FIG. 6A, in the gradient degree estimation block 44f3, the characteristic R / L shown in FIG. 3 is searched from the vehicle speed V in the block 44f31 to calculate the running resistance equivalent to the level of the vehicle 10, and the block 44f32 , The acceleration resistance is calculated based on the weight (known) of the vehicle 10 from the vehicle speed deviation ΔV (the differential value of the vehicle speed V), and is added to the running resistance corresponding to the flat ground in the addition stage 44f33, and all the travels that act on the vehicle 10 Resistance is calculated.

  Next, in the addition stage 44f34, a difference is calculated by subtracting all the calculated running resistances from the required driving force FCMD. Since the required driving force FCMD is a driving force required for the vehicle 10, if it is flat, it will be balanced with all the calculated running resistances, and the difference should be zero. Therefore, when the difference is not zero, there is a gradient resistance, that is, traveling on an uphill road, specifically, traveling on an uphill road if the difference is positive, and traveling on a downhill road if negative. Can be estimated.

  Therefore, in the multiplication stage 44f35, the estimated gradient value ASIN is calculated from the calculated gradient resistance and IW (the inertia weight of the vehicle 10). Next, in block 44f36, the gradient estimated value ASIN is input to calculate the gradient degree estimated value from the membership function shown in the figure, and the calculated gradient degree estimated value is subjected to centroid calculation (non-fuzzy calculation) to calculate the gradient degree. The FIG. 4B is an explanatory diagram showing the membership function and linguistic control rules. In block 44f36, fuzzy inference is performed from the functions and rules shown in the figure, and the degree of gradient is obtained by centroid calculation.

  FIG. 8 is an explanatory diagram showing details of the traffic jam / high speed estimation block 44f4.

  As shown in FIG. 5A, in the traffic jam / high speed estimation block 44f4, the average vehicle speed is calculated from the vehicle speed V in the block 44f41, and in block 44f42, the traffic congestion is calculated from the membership function shown in the figure using the calculated average vehicle speed. The degree estimated value and the high speed estimated value are calculated by the center of gravity calculation. FIG. 4B is an explanatory diagram showing the membership function and linguistic control rules. In block 44f42, fuzzy inference is performed from the functions and rules shown in the figure, and the degree of congestion and the high speed are obtained by the center of gravity calculation. “Congestion degree” or “high speed” indicates the degree of traffic congestion or high speed travel of the vehicle 10.

  FIG. 9 is an explanatory diagram showing processing of the motor / engine travel selection processing block 44f5.

  As shown in the figure, in the motor / engine travel selection processing block 44f5, a membership function indicating the engine travel suitability and the acceleration intention estimated value output from the engine travel suitability estimation block 44f1 and the acceleration intention estimation block 44f2 is input, Fuzzy inference is performed based on the illustrated four fuzzy rules, and a centroid operation is performed on the inference value according to the illustrated calculation formula, and the centroid operation result is integrated to calculate an integral value y.

  Next, in block 44f51, a travel request value is calculated using the threshold value. FIG. 10 is an explanatory diagram showing the threshold value in detail. In block 44f51, the integrated value y of the center of gravity calculation result is first compared with A, and when the integrated value y is equal to or greater than A, it is determined that the engine traveling request is high and traveling by the engine 12 is requested. On the other hand, when the integral value y is less than A, it is compared with B, and when the integral value y is B or less, it is determined that the motor travel request is high and travel by the second motor 26 is requested. When the integral value is less than A and exceeds B, neither engine travel request nor motor travel request is made. By providing such hysteresis, control hunting is prevented.

  In the motor / engine travel selection processing block 44f5 (that is, the fuzzy control unit 44f), when travel by the engine 12 is selected in the driving state in which the intention to accelerate increases, an imaginary line 44k in FIG. As shown, traveling by the engine 12 and traveling by the second motor 26 are both permitted, that is, acceleration assist is executed.

  FIG. 11 is an explanatory view similar to FIG. 9 showing the correction of the control rule in accordance with the gradient degree in the motor / engine travel selection process. In this case, the control rule is corrected as illustrated according to the degree of gradient.

  FIG. 12 is an explanatory graph showing a case where the membership function is corrected according to the degree of traffic jam in the motor / engine travel selection processing block 44f5. That is, when the degree of congestion is large, the membership function is corrected as indicated by a one-dot chain line or a two-dot chain line so as to expand the second motor travel area in the low speed region. As a result, the upper limit b of the fuel consumption reduction region in FIG. 3 is corrected as indicated by the imaginary line.

  FIG. 13 is an explanatory diagram showing processing of the SOC management setting block 44f6.

  In the SOC management setting block 44f6, the upper limit SOC and the lower limit SOC as shown in the figure are calculated by searching a preset table for the remaining capacity (charged state SOC) of the battery 34 from the SOC and the vehicle speed V. The

  Next, the calculated SOC is first compared with the upper limit SOC. When the calculated SOC is equal to or higher than the upper limit SOC, power generation is prohibited (however, deceleration regeneration is not prohibited). In other words, traveling by the engine 12 is not required. On the other hand, when the calculated SOC is less than the upper limit SOC, it is compared with the lower limit SOC, and when the calculated SOC is less than or equal to the lower limit SOC, it is determined that the power generation request to the second motor 26 is high, and the engine 12 is required to travel. Is done. When the calculated SOC is less than the upper limit SOC and exceeds the lower limit SOC, neither power generation prohibition nor request is performed (that is, power generation is not requested).

  FIG. 14 is a time chart showing processing of the SOC management setting block 44f6. As shown in the figure, motor travel and engine travel (power generation) are adjusted so as not to fall below the lower limit SOC. As described above, regeneration during deceleration is not limited by the upper limit SOC.

  FIG. 15 is an explanatory view similar to FIG. 13 showing parameter correction in accordance with the gradient degree in the SOC management setting process. In this case, when the slope is descending, the upper limit SOC is corrected to be low, and the frequency of power generation by the engine 12 is reduced to improve the efficiency of energy recovery during deceleration regeneration. Further, when the vehicle is climbing, the lower limit SOC is similarly corrected to be low, and the power performance when traveling on a mountain road can be improved by distributing the energy of the battery 34 to the power assist. More specifically, the SOC is corrected as shown in FIG.

  FIG. 17 is an explanatory view similar to FIG. 13, showing parameter correction according to traffic jam / high speed in the SOC management setting process. In this case, when the high speed is high, the upper limit SOC is corrected to be high, and the use width of the battery 34 is reduced to maintain a large remaining capacity, so that the vehicle is corrected for acceleration assistance during overtaking. When the degree of traffic congestion is large, the lower limit SOC is corrected to be low, the usage range of the battery 34 is expanded, and the traveling frequency of the second motor 26 at low speed is increased to improve the fuel consumption and drivability of traveling on a traffic jam road. . More specifically, the correction is made as shown in FIG.

  In the hybrid vehicle control apparatus according to this embodiment, the required driving force FCMD required by the vehicle 10 is calculated from the vehicle speed V and the accelerator pedal opening AP, and the maximum motor drive that can be output from the second motor 26 from the vehicle speed V is calculated. The motor load factor when the required driving force is borne by the maximum motor driving force is calculated, and fuzzy inference is performed from the membership function set according to the vehicle speed V with respect to the motor load factor. The travel suitability by the engine is calculated between the upper limit value b of the fuel consumption reduction region a where the fuel consumption is reduced by traveling by the second motor 26 compared to the travel and the motor maximum driving force, and the calculated travel suitability is calculated. On the basis of this, since it is configured to select one of the traveling by the engine 12 and the traveling by the second motor 26, the fuel consumption performance and the drivability are improved. It is possible to above.

  That is, the fuel consumption reduction region (motor travel region) a in which fuel consumption (fuel consumption) is reduced by traveling by the second motor 26 as compared to traveling by the engine 12 is low vehicle speed or low load traveling during cruise. However, if the travel by the second motor 26 is limited to only that region, the output width is narrow, so the threshold value of the required driving force for travel by the second motor 26 and travel by the engine 12 is narrowed, and travel switching hunting is performed. This is likely to occur, and the original performance of the second motor 26 cannot be used up. However, with the configuration as described above, when the required driving force FCMD corresponding to the maximum motor driving force of the second motor 26 is generated, it is possible to promptly switch to traveling by the engine 12, while the fuel consumption reduction region a is reliable. In addition, traveling by the second motor 26 can be selected. When the required driving force equal to or greater than the upper limit value b of the fuel efficiency reduction region a is generated, the engine 12 performs after a lapse of time corresponding to the travel suitability for the region, that is, for a long time if the required driving force is small and for a short time if large. You can switch to running. Furthermore, by calculating the running suitability between the upper limit value and the maximum driving force, not only the threshold for the required driving force, so-called play can be set and switching hunting can be prevented more reliably. Can do. Thus, drivability and fuel consumption can be improved by facilitating traveling by the electric motor in the fuel consumption reduction region.

  That is, as shown in FIG. 19, in the fuel consumption reduction region (motor travel region) a, it is possible to reliably determine the motor travel, and the maximum motor driving force reliably switches to the engine 12 and the upper limit of the fuel consumption reduction region a. The motor / engine travels based on the intention to accelerate and the engine travel suitability in the region where the value is greater than b and less than the motor maximum driving force d, and the motor travel region a has low sensitivity according to the accelerator opening AP, and the engine travel region c. In this case, since the sensitivity is increased, motor / engine switching hunting is prevented, and good drivability can be obtained.

  Also, fuzzy inference is performed from the membership function set for the rate of change of the accelerator pedal opening AP to estimate the driver's intention to accelerate, and the membership function set for the estimated acceleration intention and the calculated driving fitness The second fuzzy inference is performed to correct the travel suitability, so that, in addition to the above-described effects, when the accelerator pedal opening AP changes suddenly, the engine 12 is quickly switched (selected). ) And does not give the driver a lack of output.

  Further, fuzzy inference is performed from a membership function set in advance for the vehicle speed V to estimate traffic jam or high speed, and a target value (remaining capacity of the battery 34 (charged state SOC)) according to the estimated traffic jam / high speed ( The upper limit SOC and the lower limit SOC) are changed, so that, for example, by changing the lower limit of the target value according to traffic jam / high speed, the usage range of the battery 34 can be increased during traffic jams, and the second motor 26 This makes it possible to improve the fuel efficiency by allowing the vehicle to travel. In addition, at the time of high speed, it is possible to prepare for acceleration assistance at high speed by reducing the use width of the battery 34 and maintaining a large remaining capacity.

  That is, since the lower limit SOC is lowered on a congested road, it is possible to prioritize the energy of the battery 34 over the motor travel, and to improve fuel efficiency and drivability on the congested road. Since the upper limit SOC is increased on the high speed road, it is possible to store the energy of the battery 34 in preparation for overtaking acceleration, and the power performance can be improved in the same manner.

  Further, the estimated road gradient value is calculated from the vehicle speed V and the required driving force FCMD, and the gradient degree of the traveling road is estimated by performing fuzzy inference from a membership function set in advance for the estimated gradient value. Since the target value of the remaining capacity (charged state SOC) of the battery 34 is changed in accordance with the degree of gradient, in addition to the above-described effects, for example, if the vehicle is traveling uphill, the lower limit of the target value of the remaining capacity is changed downward. By doing so, it is possible to actively assist the power, and to improve drivability and power performance when traveling on a mountain road or the like. For example, if the vehicle is traveling on a downhill, the power generation frequency by the engine 12 can be reduced by changing the upper limit of the target value downward, and energy recovery by deceleration regeneration can be efficiently realized.

  In addition, fuzzy inference is performed from a membership function set in advance with respect to the gradient estimated value to estimate the gradient degree of the road, and based on the membership function set for the estimated gradient degree and the calculated driving fitness Since the second fuzzy inference is performed to correct the driving suitability, in addition to the above-described effects, for example, when driving downhill where the required driving force is small, it is easy to select the driving by the second motor 26 to improve fuel efficiency. On the other hand, in uphill traveling where the required driving force increases, drivability can be improved by making it easy to select traveling by the engine 12 and placing emphasis on power performance. In other words, because of the estimated gradient, priority is given to engine travel on climbing and motor travel on descending slopes, so that both power performance and fuel efficiency can be achieved even on mountain roads.

  The hybrid vehicle 10 according to this embodiment is not limited to the structure shown in FIG. 1, but may have the structure shown in FIG. While removing the second motor 26 and the PDU 32 corresponding to the second motor 26 and stopping the engine 12 (specifically, stopping the fuel supply and closing the intake and exhaust valves), the first motor 20 is You may drive and run.

  That is, the vehicle 10 includes an engine 12, a first motor 20, and a battery 34 that supplies electric power to the first motor 20 while storing electric power generated by the first motor 20. You may comprise so that it may drive | work by driving the wheel 16 with at least any one of the 1 motor 20. FIG. In FIG. 20, the engine control unit 40 and the like are not shown.

In this embodiment, as described above, power is supplied to the engine (internal combustion engine), the first and second motors 20, 26 (electric motors), and the first and second motors 20, 26, while the first, A battery (power storage means) 34 that stores electric power generated by the second motor is provided, and driving wheels (wheels) 16 are driven by at least one of the engine (internal combustion engine) 12 and the second motor (electric motor) 26. In the hybrid vehicle 10 that travels, the required driving force calculation means (MG ECU 44, blocks 44a to 44c, vehicle body model 44d) for calculating the required driving force FCMD required by the vehicle from the vehicle speed V and the accelerator pedal opening AP, the vehicle speed It calculates the maximum motor driving force which the second motor (electric motor) 26 can be output from the V, shows the percentage of the required driving force to the maximum driving force Motor load factor calculating means for calculating to motor load factor (MG ECU 44, the fuzzy control unit 44f, the engine running fit estimation block 44F1, block 44f11,44f12), membership set according to the vehicle speed for the motor load factor Perform fuzzy inference from the function, and calculate the driving suitability by the internal combustion engine between the upper limit value of the fuel consumption reduction region where the fuel consumption is reduced by traveling by the electric motor compared to the traveling by the internal combustion engine and the maximum driving force Fuzzy inference is performed from the membership function set for the rate of change of the accelerator pedal opening AP, and the internal combustion engine travel suitability calculation means (MG ECU 44, fuzzy control unit 44f, engine travel suitability estimation block 44f1, block 44f13). Acceleration intention inference to estimate driver's acceleration intention Means (MG ECU 44, fuzzy control unit 44f, acceleration intention estimation block 44f2, blocks 44f21, 44f22), fuzzy inference is performed based on the estimated acceleration intention and the membership function set for the calculated running fitness Travel request value calculating means (MG ECU 44, fuzzy control unit 44f, motor / engine travel selection processing block 44f5) for calculating the travel request value , based on the calculated travel request value , the travel by the internal combustion engine and the motor A travel selection means (MG ECU 44, fuzzy controller 44f, motor / engine travel selection processing block 44f5) for selecting one of the travels is provided.

The travel selection means is configured to select either travel by the internal combustion engine or travel by the electric motor based on the calculated integral value of the travel request value (integral value y of the gravity center calculation result) .

  In addition, when the estimated intention to accelerate increases and travel by the engine (internal combustion engine) is selected, both travel by the engine (internal combustion engine) 12 and travel by the second motor (electric motor) 26 are permitted. And permitting means (fuzzy control unit 44f, motor / engine running selection processing blocks 44f5, 44k).

  Further, a traffic jam / high speed estimation means (MG ECU 44, fuzzy control unit 44f, traffic jam / high speed estimation block 44f4, block for estimating traffic jam or high speed by performing fuzzy inference from a membership function set in advance for the vehicle speed V. 44f41, 44f42) and the remaining capacity target value change for changing the target value (upper limit SOC, lower limit SOC) of the remaining capacity (charged state SOC) of the battery (power storage means) 34 according to the estimated traffic jam / high speed. Means (MG ECU 44, fuzzy controller 44f, SOC management setting block 44f6) are provided.

  Further, a gradient estimated value of the traveling road is calculated from the vehicle speed V and the required driving force FCMD, and a gradient degree of the traveling road is estimated by performing fuzzy inference from a membership function set in advance for the gradient estimated value. Gradient degree estimating means (MG ECU 44, fuzzy control unit 44f, gradient degree estimating block 44f3, blocks 44f31 to 44f36), and remaining capacity for changing the target value of the remaining capacity of the power storage means according to the estimated gradient degree Target value changing means (MG ECU 44, fuzzy controller 44f, SOC management setting block 44f6) is provided.

  Further, a gradient estimated value of the traveling road is calculated from the vehicle speed V and the required driving force FCMD, and a gradient degree of the traveling road is estimated by performing fuzzy inference from a membership function set in advance for the gradient estimated value. Based on the gradient function estimating means (MG ECU 44, fuzzy control unit 44f, gradient degree estimation block 44f3, blocks 44f31 to 44f36), and a membership function set for the estimated gradient degree and the calculated travel suitability And a travel suitability correction means (MG ECU 44, fuzzy control unit 44f, gradient degree estimation block 44f3, engine travel suitability estimation blocks 44f5, 44f51) for performing the second fuzzy inference to correct the travel suitability. did.

1 is a schematic diagram showing an overall configuration of a hybrid vehicle control device according to a first embodiment of the present invention. FIG. It is a block diagram which shows operation | movement of the control apparatus of the hybrid vehicle shown in FIG. It is explanatory graph which shows the driving | running | working area | region of the engine and 2nd motor which are shown in FIG. It is a block diagram which shows the structure of the fuzzy control part of FIG. 2 in detail. It is explanatory drawing which shows the detail of the engine driving | running | working fitness estimation block of FIG. It is explanatory drawing which shows the detail of the acceleration intention estimation block of FIG. It is a block diagram which shows the detail of the gradient degree estimation block of FIG. It is explanatory drawing which shows the detail of the traffic congestion and high speed estimation block of FIG. FIG. 5 is an explanatory diagram showing processing of a motor / engine travel selection processing block of FIG. 4. FIG. 5 is an explanatory diagram of threshold values used in the processing of the motor / engine travel selection processing block of FIG. 4. FIG. 10 is an explanatory view similar to FIG. 9, showing correction of a control rule according to the gradient degree in the motor / engine travel selection process of FIG. 4. FIG. 5 is an explanatory graph showing a case where a membership function is corrected according to the degree of congestion in the motor / engine travel selection process of FIG. 4. It is explanatory drawing which shows the process of the SOC management setting block of FIG. It is a time chart which shows the process of the SOC management setting block of FIG. It is explanatory drawing similar to FIG. 13 which shows the parameter correction according to the gradient degree in the SOC management setting process of FIG. It is explanatory drawing which shows more concretely parameter correction according to the gradient degree in the SOC management setting process of FIG. FIG. 14 is an explanatory view similar to FIG. 13 showing parameter correction according to traffic jam / high speed in the SOC management setting process of FIG. 4. FIG. 5 is an explanatory diagram more specifically showing parameter correction according to traffic jam / high speed in the SOC management setting process of FIG. 4. FIG. 4 is an explanatory graph similar to FIG. 3 showing the effect of the apparatus of FIG. 2. It is explanatory drawing similar to FIG. 1 which shows the modification of the hybrid vehicle which concerns on this Example.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 10 Hybrid vehicle, 12 Internal combustion engine (engine), 14 Transmission, 16 Drive wheel (wheel), 20 1st electric motor (1st motor), 26 2nd electric motor (2nd motor), 30, 32 PDU, 34 Battery (power storage means), 40 engine control unit (ENG ECU), 44 management control unit (MG ECU), 52 current voltage sensor, 54 accelerator opening sensor, 56 vehicle speed sensor

Claims (6)

An internal combustion engine, an electric motor, and an electric storage unit that supplies electric power to the electric motor while storing electric power generated by the electric motor, and travels by driving wheels with at least one of the internal combustion engine and the electric motor In hybrid vehicles,
a. Requested driving force calculation means for calculating the required driving force required by the vehicle from the vehicle speed and the accelerator opening,
b. Calculates the maximum driving force which the electric motor can be outputted from the vehicle speed, motor load factor calculating means for calculating a motor load factor indicating a ratio occupied by the required driving force to the maximum driving force,
c. A fuzzy inference is performed from a membership function set according to the vehicle speed for the motor load factor, and an upper limit value of a fuel consumption reduction region in which fuel consumption is reduced by traveling by the motor as compared to traveling by the internal combustion engine, and the Internal combustion engine travel suitability calculating means for calculating travel suitability by the internal combustion engine during the maximum driving force;
d. Acceleration intention estimation means for estimating the driver's acceleration intention by performing fuzzy inference from a membership function set for the rate of change of the accelerator opening,
e. A required travel value calculation means for calculating a required travel value by performing fuzzy inference based on the estimated acceleration intention and the membership function set for the calculated travel suitability.
f . Travel selection means for selecting either travel by the internal combustion engine or travel by the electric motor based on the calculated travel request value ;
A control apparatus for a hybrid vehicle, comprising: The travel selecting means, based on the integral value of the calculated running requirements value, the control device for a hybrid vehicle according to claim 1, wherein the selecting one of the running by the running and the electric motor by the internal combustion engine . g. Permission means for permitting both traveling by the internal combustion engine and traveling by the electric motor when the estimated intention to accelerate increases and traveling by the internal combustion engine is selected;
The control apparatus for a hybrid vehicle according to claim 1, further comprising: h. A traffic jam / high speed estimation means for estimating traffic jam or high speed by performing fuzzy inference from a membership function preset for the vehicle speed,
And i. A remaining capacity target value changing means for changing a target value of the remaining capacity of the power storage means according to the estimated traffic jam / high speed;
The control apparatus of the hybrid vehicle in any one of Claim 1 to 3 characterized by the above-mentioned. j. Gradient degree estimation that calculates a gradient estimated value of the traveling road from the vehicle speed and the required driving force, and estimates a gradient degree of the traveling road by performing fuzzy inference from a membership function set in advance for the gradient estimated value means,
And k. A remaining capacity target value changing means for changing a target value of the remaining capacity of the power storage means according to the estimated gradient degree;
The control apparatus of the hybrid vehicle in any one of Claim 1 to 4 characterized by the above-mentioned. l. Gradient degree estimation that calculates a gradient estimated value of the traveling road from the vehicle speed and the required driving force, and estimates a gradient degree of the traveling road by performing fuzzy inference from a membership function set in advance for the gradient estimated value means,
And m. A running fitness correction means for correcting the running fitness by performing a second fuzzy inference based on the estimated gradient degree and a membership function set for the calculated running fitness;
The control device for a hybrid vehicle according to any one of claims 1 to 5, further comprising:

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