Output control method and control system of a power source for a vehicle

Abstract: A method of controlling output of a power source for a vehicle, for determining the amount of manipulation of a secondary output regulation means for directly regulating output of the power source, based on the amount of manipulation of a primary output regulation means manipulatable by a user: The relation between the amount of manipulation of said primary output regulation means and that of said secondary output regulation means can be changed based on any of at least user properties, driving conditions, change of driving environment, or deterioration of the power source over time

Description: This invention relates to a method and a control apparatus for controlling an output of a power source for a vehicle. The power source carrying vehicle powered by an engine or a motor, is provided with a primary output regulation means, such as an accelerator pedal, accelerator lever, or accelerator grip, for regulation of output of these power sources by the user, and this primary output regulation means actuates a secondary output regulation means, such as a throttle valve for directly regulating output of the power source or a control section for controlling an energization current to the motor, so as to adjust output of the power source finally. The amount of manipulation of the primary output regulation means and that of the secondary output regulation means are determined at the load to be in a given fixed relation, therefore if the accelerator grip, for example, is adjusted at a certain rotation angle, the throttle valve opening is basically the same every time, and the movement of the throttle valve in response to that of the accelerator lever has been always constant. The foregoing relation between the primary output regulation means and the secondary output regulation means represents the output performance of the power source carrying vehicle directly; for example, the larger throttle opening relative to the rotation angle of the accelerator grip represents a power oriented type because it results in a higher output, while the smaller throttle opening represents a fuel consumption oriented type because it results in a lower output, and the larger movement of the throttle valve relative to that of the accelerator grip represents a response oriented type, while the smaller movement of the throttle valve represents a riding feeling oriented type because it results in a smaller output change. Since the above described preference to the output performance of the power source carrying vehicle varies for each user, if the relation between the primary output regulation means and the secondary output regulation means is determined at the load to be in a given fixed relation, a problem is raised that individual user preference is not reflected. In addition to the foregoing problem, the power source carrying vehicle is used in the various circumstances, the driving conditions being different for each user, and further, since the power source (including peripheral members) also deteriorates over time as a result of use, another problem is raised that the relation between the primary output regulation means and the secondary output regulation means, which has been determined at the load, cannot necessarily be kept optimum. US-A-5,477,825 and US-A-5,532,929 relate to a driving power control apparatus and, accordingly, an engine control comprising a neuro computer and a throttle computer for controlling an angle of a throttle valve. Here, the neuro computer learns a relationship among a manipulation amount of an accelerator pedal, a vehicle speed and an acceleration and outputs a requested-acceleration model. Furthermore, the neuro computer compares the "requested-acceleration model" with a "reference acceleration model" previously learned and determines a throttle sensitivity from the difference between the "requested-acceleration model" and the "reference-acceleration model". Finally, the throttle computer controls the opening of a throttle valve based on the determined throttle sensitivity, so that a range of manipulation of accelerator pedal could be varied in order to obtain different acceleration by the same manipulation of the accelerator pedal, wherein a driver has no possibility to effect directly the control process. Accordingly, it is an objective of the present invention to provide a method as well as a control apparatus for controlling an output of a power source of a vehicle, so as to allow output characteristics of the vehicle to be adapted to characteristics matched with user preference and a possibility of exertion of influence on the control process by the user. According to the present invention, this objective is solved by a method according to the features of claim 1. According to the present invention, the above-mentioned objective is further solved by a control apparatus according to the features of claim 9. Further preferred embodiments of the present invention are laid down in the further subclaims. In the following, the present invention is explained in greater detail by means of several embodiments thereof in conjunction with the accompanying drawings, wherein: Fig. 1 is a schematic diagram illustrating the relation between the engine and the control unit for executing the output control method; Fig. 2 is a schematic block diagram illustrating the internal structure of the control unit; Fig. 3 shows diagrams illustrating several examples of the static characteristics of the throttle; Fig. 4 shows diagrams illustrating several examples of the dynamic characteristics of the throttle; Fig. 5 is a schematic block diagram of the evolution control section; Fig. 6 is a schematic block diagram illustrating the structure of the electronic throttle control Module; deterioration of the power source over time; and an evaluation value input device for inputting an evaluation value by the user for affecting the means for evolutionally altering and the control unit. Thus, as mentioned above a control of the output of the power source in response to the user properties, running conditions of the power source, change of driving environment, or deterioration of the power source or its peripheral members may be facilitated. Further preferred embodiments of the present invention are laid down in the further subclaims. In the following, the present invention is explained in greater detail by means of several embodiments thereof in conjunction with the accompanying drawings, wherein: Fig. 1 is a schematic diagram illustrating the relation between the engine and the control unit for executing the output control method; Fig. 2 is a schematic block diagram illustrating the internal structure of the control unit; Fig. 3 shows diagrams illustrating several examples of the static characteristics of the throttle; Fig. 4 shows diagrams illustrating several examples of the dynamic characteristics of the throttle; Fig. 5 is a schematic block diagram of the evolution control section; Fig. 6 is a schematic block diagram illustrating the structure of the electronic throttle control Module; Fig. 7 is a diagram showing a specific example of the control Module in the evolutional adaptation layer; Fig. 8 is a flow chart showing the flow of evolutional processing of the control Module using a genetic algorithm; Fig. 9 is a conceptional view showing an example of an individual with the bonding factors of the neural network coded as genes; Fig. 10 is a conceptional view showing how to achieve the teacher data for use in the learning control Module in the learning layer; Fig. 11 is a conceptional view showing learning in the learning layer through a CMAC, using only the new teacher data; Fig. 12 is a schematic flow chart illustrating the general flow of evolutional processing in the evolution control section; Fig. 13 is a schematic drawing illustrating the relation between an electric motor and a control unit executing the output control method; Fig. 14 is a schematic block diagram illustrating the internal structure of the control unit; Fig. 15 is a schematic block diagram illustrating the general structure of the motor energization control section; Fig. 16 shows diagrams illustrating several examples of the static characteristics of the throttle; Fig. 17 shows diagrams illustrating several dynamic characteristics during electric motor driving; Fig. 18 shows diagrams illustrating several dynamic characteristics during regeneration of the electric motor; and Fig. 19 is a schematic block diagram of the evolution control section. Figs. 1-12 show an embodiment of the method of controlling output of a power source carrying vehicle according to the invention (hereinafter referred to simply as output control method), as applied to an internal combustion engine with an electronic throttle. Fig. 1 is a schematic diagram illustrating the relation between the engine and the control unit for executing the output control method. The engine shown in the figure is provided with the so-called electronic throttle adapted to detect the amount of manipulation of the accelerator grip by user through an accelerator manipulation detection sensor, to drive a stepping motor according to the accelerator manipulation quantity detected, and to adjust the opening of the throttle valve by means of the stepping motor. The control unit is adapted to input signals of crank angle and accelerator manipulation quantity obtained from a crank angle sensor in the engine and an accelerator manipulation detecting sensor in the accelerator grip, and to determine, for outputting, drive signals of the stepping motor based on these input signals. Fig. 2 is a schematic block diagram illustrating the internal structure of the control unit. As shown in Fig. 2, the control unit is provided with an engine speed calculation section and an evolution control section, the engine speed calculation section calculating the engine speed based on the crank angle signals. The evolution control section is adapted to input the engine speed calculated at the engine speed calculation section and the accelerator manipulation quantity signals, and to determine, for outputting, drive signals of the stepping motor based on these input information. In addition, as shown in Figs. 1 and 2, user evaluation information is inputted to the evolution control section of the control unit through a button type evaluation value input device, and the evolution control section is arranged such that it evolutionally alters, based on this user evaluation information, the relation between the input and output information, that is, the drive characteristics of the throttle valve to the amount of accelerator manipulation by user, to thereby allow the output characteristics of the vehicle carrying the engine to be adapted to the characteristics matched with user preference. Now, referring briefly to the characteristics of the electronic throttle valve to the amount of accelerator manipulation, they include static characteristics and dynamic ones. The static characteristics represent the relation between accelerator manipulation quantity and throttle valve opening at the time of constant accelerator manipulation quantity (i.e. rotation angle of the manipulated accelerator grip), which affect the regular running characteristics of the vehicle. Thus, by changing the static characteristics, various throttle valve opening styles can be obtained through the same rotation angle of the manipulated accelerator grip, as shown in Fig. 3, such as a low opening quick acceleration type (see Fig. 3(a)) in which the electronic throttle valve is opened wide when the rotation angle of the manipulated accelerator grip is small, and the throttle valve approaches gradually the full throttle position as the rotation angle of the manipulated accelerator grip is increased; a proportional type (see Fig. 3(b)) in which the rotation angle of the manipulated accelerator grip is in proportion to the throttle opening; or a high opening quick acceleration type (see Fig. 3(c)) in which the throttle valve is opened gradually when the rotation angle of the manipulated accelerator grip is small, and it is opened quickly to the full throttle position as the rotation angle of the manipulated accelerator grip becomes large. Any function may be used for the static characteristics as long as the throttle valve opening is increased or invariable with increasing amount of accelerator manipulation and the throttle valve opening is zero when the accelerator manipulation quantity is zero. Thus, by changing the static characteristics, a different throttle valve opening can be outputted in relation to the same amount of accelerator manipulation. The dynamic characteristics represent the relation of the change in accelerator manipulation quantity vs. the change in throttle valve opening, which affect the transient characteristics of the vehicle. Specifically, the dynamic characteristics can be changed by combining a primary delay filter and an incomplete differential filter and altering the parameters of these filters. Thus, by changing the throttle opening, various types of the dynamic characteristics can be obtained, as shown in Fig. 4, such as a low response type (see Fig. 4(a)) in which the throttle valve is opened relatively slowly in relation to the accelerator manipulation, a high response type (see Fig. 4(b)) in which the throttle valve is opened promptly in spite of some spikes being generated upon manipulation of the accelerator, and an intermediate type (see Fig. 4(c)) which has the intermediate characteristics between foregoing two types. Now, the structure of the evolution control section will be described in detail. characteristic set at the static characteristic altering section, and to determine, for outputting, the opening of the electronic throttle valve from the virtual accelerator input X2 at the dynamic characteristic altering section. In Fig. 6, X1 represent the control accelerator manipulation quantity (accelerator manipulation signal), X2 the virtual accelerator input, y the opening of the accelerator valve, f the static characteristic function, T the primary delay constant, Td the differential time, α the acceleration correction factor, and η the differential gain, of which the static characteristic function, primary delay constant, acceleration correction factor, differential time, or differential gain is a variable parameter, but in this embodiment, description will be made by giving examples in which the static characteristic function is to be selected by user from among several pre-arranged functions, the differential gain of the dynamic characteristics is fixed, the primary delay time constant, accelerator correction factor, and differential time are evolved. In the following description, the primary delay time constant, acceleration correction factor, and differential time are referred to generally as electronic throttle control parameters. The electronic throttle control parameter initial value setting section determines, for outputting, initial values of the foregoing primary delay time constant T, acceleration correction factor a, and differential time Td. (Regarding the evolutional adaptation layer) In the evolutional adaptation layer, correction values of the electronic throttle control parameters are evolved such that the electronic throttle control parameters in the reflection layer evolve adaptively to the user preference. As shown in Fig. 5, the evolutional adaptation layer consists of an evaluation section and an evolutional adaptation section. The evolutional adaptation section is provided with control Modules for determining electronic throttle control parameter correction values in the reflection layer; and in the The electronic throttle control parameter initial value setting section determines, for outputting, initial values of the foregoing primary delay time constant T, acceleration correction factor α, and differential time Td. (Regarding the evolutional adaptation layer) In the evolutional adaptation layer, correction values of the electronic throttle control parameters are evolved such that the electronic throttle control parameters in the reflection layer evolve adaptively to the user preference. As shown in Fig. 5, the evolutional adaptation layer consists of an evaluation section and an evolutional adaptation section. The evolutional adaptation section is provided with control Modules for determining electronic throttle control parameter correction values in the reflection layer; and in the Drabili evaluation section, evaluation for each individual is performed on the basis of user evaluation when control Modules in the evolutional adaptation section are evolved using a genetic algorithm. Fig. 7 is a diagram showing a specific example of the control Module in the evolutional adaptation layer. As shown in the figure, the control Module is composed of a two input-three output type neural network with normalized acceleration manipulation quantity and normalized engine speed, as input information, and with electronic throttle control parameters in the reflection layer, that is, correction quantity AT, A α, ATd of the primary delay time constant T, acceleration correction factor α, and differential time Td, as output information. In the evolutional adaptation layer, bonding load of the neural network constituting each Module in the evolutional adaptation section is coded as genes to produce a number of chromosomes (individuals), the produced individuals are selected according to evaluation in the evaluation section and the remaining individuals are crossed with each other to produce individuals of the next generation, and further, selection of these individuals are repeated, thereby evolving each control Module in the evolutional adaptation section such that it is matched with the evaluation in the evaluation section. The foregoing evolutional processing will be described more in detail. Fig. 8 is a flow chart showing the flow of evolutional processing of the control Module using a genetic algorithm. Firstly, as shown in Fig. 9, the bonding factors of the neural network constituting the control Module is coded as genes to produce the first generation consisting of a plural number of individuals a(n) (n=10 in this embodiment) (Step 1). Here, for the values of genes for each individual (i.e., values of the bonding factors of the neural network), initial values are determined at random within the predetermined range (approximately between -10 and 10). At this time, if the learning layer has already completed learning and generated output, diversity of the population during evolutional processing can be maintained without any damage of performance even when the number of individuals is limited, by including one individual which can reduce the output of the evolutional adaptation layer to zero. Secondly, the bonding load of the neural network of the control Module is fixed with the bonding load of one, for example, individual a(1), of individuals a(n) produced in Step 1, to determine the output AT, A α, ATd of the neural network to the actual input information (engine speed and accelerator manipulation amount) (Step 2), and further, this output is linear transformed using equations (P3), to determine the output ATy1, Aαy1, ATdy1 (i.e. electronic throttle valve control parameter correction quantity) for the individual an(1) (Step 3). Engine speed and accelerator manipulation quantity of the input information are used in the normalized form, respectively. ATy1 = 2XGAT-G Acty1 = 2XG α-G of the learning layer (Step 5), evaluation of individual a(1) by user is inputted (Step 6), and the evaluation value of adaptation of individual a(1) is determined (Step 7). The output of the learning layer is set to zero initially, but after the evolutional processing has been completed in the evolutional adaptation layer, the learning layer may be arranged such that the results of its evolution are to be learned. Detailed description of the learning layer will be given later. The evaluation of the individual by user in Step 6 as described above may be inputted through an evaluation value input device formed in a push button shape for manipulation during driving. Specifically, for example, when a driver presses the button, the evaluation value of the individual is determined based on the length of time the button is pressed, at Step 7. The methods of calculating the evaluation value at Step 7 include, for example, a method of multiplying the reciprocal of the pressing time by a certain factor, or a method of calculating the value from the length of pressing time using Fussy Rule. In this way, a relatively accurate evaluation value can be obtained in spite of vagueness of human evaluation. In addition, if the user continue to press the button over a predetermined time, individuals under evaluation at that point of time may be eliminated. Thus, the driver can eliminate individuals with unfavorable characteristics immediately and the individual does not affect the next generation, thereby providing a high speed evolution. This processing of Steps 6, 7 is performed in the evaluation section. Processing from Step 2 to Step 7 as described above is performed on all the individuals produced at Step 1, and when it is determined that adaptation of all the individuals is evaluated (Step 8), determination is made whether or not a predetermined generation number evolutional processing has been performed (Step 9). When evolutional processing has not been performed over the predetermined number of generation, selection is performed of parent individuals of the next generation from ten individuals produced at Step 1 (Step 10). In this selection, a roulette type selection method is used and a number of parent individuals are probabilistically selected with probability in proportion to adaptation of each individual. button over a predetermined time, individuals under evaluation at that point of time may be eliminated. Thus, the driver can eliminate individuals with unfavorable characteristics immediately and the individual does not affect the next generation, thereby providing a high speed evolution. This processing of Steps 6, 7 is performed in the evaluation section. Processing from Step 2 to Step 7 as described above is performed on all the individuals produced at Step 1, and when it is determined that adaptation of all the individuals is evaluated (Step 8), determination is made whether or not a predetermined generation number evolutional processing has been performed (Step 9). When evolutional processing has not been performed over the predetermined number of generation, selection is performed of parent individuals of the next generation from ten individuals produced at Step 1 (Step 10). In this selection, a roulette type selection method is used and a number of parent individuals are probabilistically selected with probability in proportion to adaptation of each individual. If excessively exact generation change is applied in this case, individuals of high evaluation may be destroyed, therefore elite preservation strategy is also employed in which the elite (individual of highest evaluation) is left unconditionally to the next generation. In addition, linear transformation of adaptation is performed as appropriate such that the ratio of the highest adaptation to the mean adaptation in the plural number of individuals is constant. After the selection of parent individuals has been completed, crossing is performed of selected individuals as parent individuals, and the second generation consisting of ten child individuals is produced again (Step 11). A method such as one point crossing, two point crossing, or normal distribution crossing is used in crossing between individuals. Normal distribution crossing is a method in which children are produced according to the normal distribution rotation-symmetrical to the axis connecting parents with number of generations have been reached. Thus, child individuals constituting each generation are selected according to evaluation in the evaluation section, that is, user preference, and the next generation is produced, so that the input and output relation of the first control Module will evolve gradually so as to be matched with user preference. The determination is made at Step 9 of whether or not a predetermined number of generations have been reached; when it is determined that the generation is the last one, the individual of the highest adaptation (optimum individual), that is one elite, from among ten child individuals of the generation is selected (Step 12); the bonding factors of the neural network in the control Module are fixed with above-mentioned genes constituting the optimum individual (Step 13); and then, the procedure proceeds to learning processing on the learning control Module in the learning layer. (Regarding the learning layer) Now, the learning layer will be described in detail. The learning layer is adapted to learn the output of the control Module after evolution, achieved in the evolutional adaptation layer (in this embodiment, electronic throttle control parameter correction quantity) and to reflect the output of the evolutional adaptation layer to the reflection layer even after completion of the evolutional processing. In the case of the information that the output of the control Module of the evolutional adaptation layer does not depend on the driving conditions of the vehicle, that is, in the case where there is no information on the driving conditions in the input of the control Module, the learning layer may only output the value of the output of the control Module of the evolutional adaptation layer added to that of the learning layer. However, in the case of the information that the output of the control Module of the evolutional adaptation layer depends on the driving conditions of the vehicle, since the relation between the driving conditions of the vehicle and the output of the control Module of the evolutional adaptation layer must also been learned in the learning layer, the learning layer is provided with a control Module for learning and a control Module for execution. In the case of this embodiment, the control Module of the evolutional adaptation layer is composed of a neural network in which engine speed, one of the driving conditions of the vehicule, is input information, therefore the learning layer takes the form of the latter. The learning layer is adapted to learn the output of the control Module after evolution, achieved in the evolutional adaptation layer (in this embodiment, electronic throttle control parameter correction quantity) and to reflect the output of the evolutional adaptation layer to the reflection layer even after completion of the evolutional processing. In the case of the information that the output of the control Module of the evolutional adaptation layer does not depend on the driving conditions of the vehicle, that is, in the case where there is no information on the driving conditions in the input of the control Module, the learning layer may only output the value of the output of the control Module of the evolutional adaptation layer added to that of the learning layer. However, in the case of the information that the output of the control Module of the evolutional adaptation layer depends on the driving conditions of the vehicle, since the relation between the driving conditions of the vehicle and the output of the control Module of the evolutional adaptation layer must also been learned in the learning layer, the learning layer is provided with a control Module for learning and a control Module for execution. In the case of this embodiment, the control Module of the evolutional adaptation layer is composed of a neural network in which engine speed, one of the driving conditions of the vehicle, is input information, therefore the learning layer takes the form of the latter. Thus, the learning layer is provided with a control Module corresponding to that of the evolutional adaptation layer, which Module, not shown in the figure, consists of two control Modules and arranged such that while one of the two Modules acts for execution of control, the other Module acts for learning, the functions of the two Modules being interchangeable with each other. Any type of control Module may be used, if it is capable of learning, for example, a neural network or a C MAC type. In the learning layer, when evolutional processing is performed for each Module in the evolutional adaptation layer over a predetermined number of generations, and the neural network constituting the Module is fixed with the optimum bonding factor at that point of time, a teacher data is achieved by combining the relation between input and output of the control Module of the evolutional adaptation layer with the relation, acting for execution, between input and output of the control Module of the learning layer. Specifically, as shown in Fig. 10, the data of input and output of the evolutional adaptation layer and the learning layer is averaged in a certain step width, and the resulting value is adopted as a teacher data. For example, if mean engine speed in a second is 5000 rpm and mean opening is 20%, then these values are added to the electronic throttle control parameter correction quantity of the evolutional adaptation layer and learning layer at the time to make the teacher data. Also, the time the teacher data was prepared, is recorded and the record is arranged such that the data with newer time record is considered to be more important as a teacher data. Upon achieving the teacher data of the control Module, the learning control Module in the learning layer start learning, based on the teacher data achieved, and learning is completed at the time when the difference between the output of the learning control Module, and that of the executing control Modules in the evolutional adaptation and learning layers, is smaller than a threshold value. After completion of learning, the learning control Module is replaced with a Module for execution, the output of each control Module of the evolutional adaptation layer is set to zero or to the next evolutional processing output. During learning in the learning control Module, the control Module of the evolutional adaptation layer continues to output the electronic throttle control parameter correction quantity, with the control Module of the evolutional adaptation layer fixed with the optimum bonding factor, and the electronic throttle control parameter, corrected with correction quantity having a value of the output of the evolutional adaptation layer added to the output of the executing control Module of the learning layer, is used in calculation at the electronic throttle control Module in the reflection layer. The initial value of the executing control Module in the learning layer is set such that its output is always zero. Thus, control in the reflection layer can be performed initially, using only the output of the evolutional adaptation layer. Information of the control Module learned in the learning layer can be stored in an internal storage means or an external storage means, etc. which allows the user to call the stored characteristics as required, and to run the vehicle. Thus, the condition that the results of learning can be stored and called, allows flexible response to the change of mental state of the user. In the case where the control Module in the foregoing learning layer is a neural network, learning is performed in an ordinary method, while in the case where the control Module consists of a CMAC, it is possible to learn only the portion corresponding to the newly achieved teacher data, thus enhancing learning efficiency. Referring briefly to the flow of evolutional processing in the evolution control section described above, upon starting evolutional processing, the evolution control section first set the throttle static characteristic as shown in Fig. 12 (Step 1). This setting of the static characteristic may be performed by user selecting it from among a number of pre-arranged static characteristics, or a specific static characteristic may be set in advance. Upon setting the static characteristic, the evolutional adaptation layer evolves the control Module while repeating the production, evaluation, and selection of individuals as described above, and after a predetermined number of generations has been reached, the results of its evolution is learned in the learning layer (Step 2). After completion of learning in the learning layer, the evolutional adaptation layer stops its output, and electronic throttle control by the reflection layer and learning layer, that is, control using electronic throttle control parameters corrected with correction values outputted from the learning layer, is performed (Step 3). Thereafter, the evolutional adaptation layer is activated at certain time intervals to evaluate Drabili performance. If the performance is not improved, the control by the reflection layer and learning layer is continued, and if the performance is improved, evolutional processing is automatically resumed from Step 2. The evolutional processing may be arranged such that it starts immediately after engine starting, or it starts according to instruction by user. Also, as in this embodiment, the evolutional processing may be arranged such that once it has been completed, the evolutional adaptation layer is activated at certain time intervals and the evolutional processing is resumed upon improvement of performance, or it may be arranged such that it starts according to instruction by user every time. Next, an embodiment of the output control method according to this invention is shown, as applied to electric motor drive control in a vehicle of an electric motor drive type. Fig. 13 is a schematic drawing illustrating the relation between an electric motor and a control unit executing the output control method. The electric motor shown in the figure is a three-phase ac servo-motor; the control unit detects the amount of accelerator grip (not shown) manipulation by user through an accelerator manipulation quantity detection sensor, energization current from battery to motor being determined, based on the detected accelerator manipulation quantity. Fig. 14 is a schematic block diagram illustrating the internal structure of the control unit. As shown in Fig. 14, the control unit comprises a motor speed and magnetic polar position calculation section for calculating motor speed and magnetic polar position based on encoder signals; a motor current instruction value calculation section (evolution control section) for determining current instruction value to the motor based on accelerator manipulation quantity detected by an accelerator manipulation quantity detection sensor; and an energization control section for converting dc current from the battery to ac current based on the motor current instruction obtained from the motor current instruction value calculation section and feeding the electric motor with ac current of different phase. Fig. 15 is a block diagram illustrating the general structure of the motor energization control section, which comprises, as shown in the figure, a current control calculation section for controlling current to the motor based on the motor current instruction value from the motor current instruction value calculation section (evolution control section) and the fed-back motor currents 1,2; a PWM wave form generating section for generating a PWM wave form based on control signals outputted from the current control calculation section; and a gate drive circuit. In addition, as shown in Figs. 13 and 14, user evaluation information is inputted to the motor current instruction value calculation section (evolution control section) of the control unit through a button type evaluation value input device, and the motor current instruction value calculation section (evolution control section) is arranged such that it evolutionally alters, based on this user evaluation information, the relation between the input and output information, that is, the electric motor current instruction value to the amount of accelerator manipulation by user, to thereby allow the output characteristics of the vehicle carrying the engine to be adapted to the characteristics matched with user preference. Now, referring briefly to the characteristics of the electric motor current instruction value to the amount of accelerator manipulation, this characteristics include static characteristics and dynamic ones. The static characteristics represent the relation between accelerator manipulation quantity and current instruction value at the time of constant amount of accelerator manipulation (i.e., rotation angle of the manipulated accelerator grip), which affect the regular running characteristics of the vehicle. By changing the static characteristics, various energization current styles can be obtained through the same rotation angle of the manipulated accelerator grip, as shown in Fig. 16, such as a low opening quick acceleration type (see Fig. 16(a)) in which the energization current is relatively large when the rotation angle of the manipulated accelerator grip is small, and the energization current approaches the maximum value as the rotation angle of the manipulated accelerator grip is increased; a proportional type (see Fig. 16(b)) in which the rotation angle of the manipulated accelerator grip is in proportion to the energization current; or a high opening quick acceleration type (see Fig. 16(c)) in which the energization current is increased gradually when the rotation angle of the manipulated accelerator grip is small, and it is increased quickly up to the maximum value as the rotation angle of the manipulated accelerator grip becomes large. Any function may be used for the static characteristics if the energization current is increased or invariable with increasing amount of accelerator manipulation and the energization current is zero when the accelerator manipulation quantity is zero, and thus a different energization current can be outputted in relation to the same amount of accelerator manipulation by changing the static characteristics. The dynamic characteristics represent the relation of the change in accelerator manipulation quantity v.s. the change in current instruction value, which affect the transient characteristics of the vehicle. Specifically, the characteristics can be changed by combining a primary delay filter and an incomplete differential filter and altering the parameters of these filters. Fig. 17 shows several dynamic characteristics during driving of the electric motor, and Fig. 18 those during regeneration of the same. Now, the structure of the evolution control section will be described in detail. Fig. 19 is a schematic block diagram of the evolution control section. As shown in the figure, the evolution control section, similar to the first embodiment, consists of a reflection layer, learning layer, and evolutional adaptation layer. The reflection layer consists of a motor control Module and a motor control parameter initial value setting section. The motor control Module is, similar to the first embodiment, provided with a static characteristic altering section, and a dynamic characteristic altering section consisting of a primary delay filter and an incomplete differential filter, which Module is adapted to input the actual accelerator manipulation quantity to transform the same to a virtual (e.g., primary delay time constant, acceleration correction factor, differential time, or static characteristic function, etc.) in the reflection layer. In the evolutional adaptation layer, bonding load of the neural network constituting each Module in the evolutional adaptation section is coded as genes to produce a number of chromosomes (Individuals), the produced individuals are selected according to evaluation in the evaluation section and the remaining individuals are crossed with each other to produce individuals of the next generation, and further, selection of these individuals are repeated, thereby evolving each control Module in the evolutional adaptation section such that it is matched with the evaluation in the evaluation section. The evolutional processing using a genetic algorithm in the evolutional adaptation layer is basically the same as that of the first embodiment and detailed description is omitted. The learning layer is, similar to the first embodiment, provided with a learning neural network and an executing neural network, and arranged such that while control is performed in the execution neural network, information, on which evolutional processing has been completed, is learned in the learning neural network and upon completion of learning, the learning neural network is replaced with the executing neural network. As described in the first and second embodiment, by evolving the relation between manipulation quantity of the accelerator grip as a first output regulation means and drive quantity of the stepping motor for driving the throttle valve as a second output regulation means or energization current signals to the control section for executing energization control on the electric motor, output performance matched with each user preference can be obtained and the user himself is able to select individuals under evolution, thus providing pleasurable user feeling as if he was training the vehicle. Although, in the foregoing embodiment, a method has been described in which the static characteristics of the secondary, output regulation means (stepping motor or energization control section) to the primary output regulation means (accelerator manipulation quantity), are set by user in advance and only the dynamic characteristics each other to produce individuals of the next generation, and further, selection of these individuals are repeated, thereby evolving each control Module in the evolutional adaptation section such that it is matched with the evaluation in the evaluation section. The evolutional processing using a genetic algorithm in the evolutional adaptation layer is basically the same as that of the first embodiment and detailed description is omitted. The learning layer is, similar to the first embodiment, provided with a learning neural network and an executing neural network, and arranged such that while control is performed in the execution neural network, information, on which evolutional processing has been completed, is learned in the learning neural network and upon completion of learning, the learning neural network is replaced with the executing neural network. As described in the first and second embodiment, by evolving the relation between manipulation quantity of the accelerator grip as a first output regulation means and drive quantity of the stepping motor for driving the throttle valve as a second output regulation means or energization current signals to the control section for executing energization control on the electric motor, output performance matched with each user preference can be obtained and the user himself is able to select individuals under evolution, thus providing pleasurable user feeling as if he was training the vehicle. Although, in the foregoing embodiment, a method has been described in which the static characteristics of the secondary, output regulation means (stepping motor or energization control section) to the primary output regulation means (accelerator manipulation quantity), are set by user in advance and only the dynamic characteristics are evolved, the method of evolution is not limited to this embodiment, but a control Module having the static and dynamic characteristics collected in the evolutional adaptation layer may be provided to evolve the combined whole, or control Modules corresponding to the static and dynamic characteristics may be provided separately in the evolutional adaptation layer to be evolved respectively. In addition, if control Modules corresponding to the static and dynamic characteristics are provided separately in the evolutional adaptation layer, evolutional processing may be performed in parallel, or either of the Modules, preferably the static characteristics, may be evolved first, and thereafter, evolutional processing may be performed on the other control Module with fixed control Module after evolution. Further, although in this embodiment, the evolutional processing on each control Module is arranged such that it is completed when evolution of a predetermined number of generations has been completed, determination of completion of the evolutional processing is not limited to this embodiment, but the evolutional processing may be arranged such that each Module is evolved in succession until the evolution converges. Furthermore, although in this embodiment, a push button type input device is provided and user evaluation on each individual is determined according to the length of time the user presses the button, the method of determining the user evaluation is not limited to this embodiment, but any method can be used for determination, and for example, the characteristics of all individuals may be visually represented during evolutional processing, and individuals of high evaluation may be selected by user directly from those characteristics. Also, although in this embodiment, selection of individuals is made according to user preference during evolutional processing, the method of selection is not limited to this embodiment, but evaluation on each individual may be made, based on the driving condition of the vehicle, change of the driving environment, or deterioration of the power source over time. Specifically, the driving condition such as running on the congested road, mountainous road, free way, or city road may be determined, for example, from manipulation pattern of the throttle or the brake, and evaluation criteria may be changed from these information data. The evaluation criteria may be changed such that in the case of congested road, for example, higher evaluation is given for lower response and higher fuel consumption, and in the case of mountainous road, higher evaluation for higher response and lower fuel consumption, as the case may be. Further, measurement of the atmospheric temperature, humidity, or atmospheric pressure may be made to determine the driving environment, and evaluation criteria may be changed from the results of the determination. In addition, for example, output drop due to change in mounting state of the engine, wear of a cam on the cam shaft, or wear of the piston ring, etc., may be monitored to determine the deterioration of the power source over time, and evaluation criteria may be changed from the results of the determination. Furthermore, although in the foregoing embodiment, a method of controlling output of the power source mounted on a vehicle has been described, the object is not limited to this embodiment, but this method may be applied to any vehicle if it carries some kind of power source, for example, also to outboard engines. As described above, the output control method in a power source carrying vehicle according to this invention is characterized by a method of controlling output of a power source mounted on a power source carrying vehicle, for determining the amount of manipulation of a secondary output regulation means for directly regulating output of the power source, based on the amount of manipulation of a primary output regulation means manipulatable by a user, wherein the relation between the amount of manipulation of said primary output regulation means and that of said secondary regulation means is adapted to evolve through a genetic algorithm based on any of at least user properties, driving conditions, change of driving environment, or deterioration of the power source over time. Therefore, the relation between the amount of manipulation of the primary output regulation means and that of the secondary regulation means can be adaptively changed so as to be matched with any of user properties, driving conditions, change of driving environment, or deterioration of the power source over time, so that if the relation is evolved, for example, on the basis of the characteristic of difference of the driving conditions, the preference, skill, or condition of a user can be reflected to the output performance of the power source carrying vehicle; if the relation is evolved on the basis of driving conditions or driving environment, output control can be performed in accordance with driving conditions or driving environment (climate or temperature in a region where the vehicle is in use); and further, if the relation is evolved, on the basis of deterioration of the power source over time, optimum output control can be performed in accordance with deterioration of the power source. In addition, if the static characteristics between the amount of manipulation of the primary output regulation means and that of the secondary output regulation means are evolved, the driving characteristics during normal running of the power source carrying vehicle can be evolved, so that the driving characteristics during transient driving of the power source carrying vehicle can be evolved by changing the dynamic characteristics. Further, if the primary delay and/or differential characteristics between the amount of manipulation of the primary output regulation means and that of the secondary regulation means are evolved, response performance of the power source carrying vehicle can be evolved significantly. Furthermore, if the relation between the amount of manipulation of the primary output regulation means and that of the secondary regulation means is evolved on the basis of any of at least the preference, skill, or condition of a user, the output characteristics matched with the preference, skill, or condition of the user can be obtained, thus providing a pleasurable user feeling of training the vehicle. Even further, if an input device suitable for user input is provided and the foregoing user preference is determined, based on the length of time the user manipulates the input device, relatively accurate evaluation values can be obtained in spite of vagueness of human evaluation, thus providing effective utilization of the genetic algorithm.

Claims: A method for controlling an output of a power source of a vehicle, comprising the steps of: determining an amount of manipulation of a secondary output regulation means for directly regulating output of the power source, based on an amount of manipulation of a primary output regulation means manipulatable by a user, evolutionally altering a relation between the amount of manipulation of the primary output regulation means and of the secondary output regulation means, changing the relation between the amount of manipulation of the primary output regulation means and of the secondary output regulation means based on any of at least user properties, driving conditions, change of driving environment, or deterioration of the power source over time, characterised in that during evolutionary altering the relation between the amount of manipulation of the primary and secondary output regulation means individuals are generated by the evolutional processing using a genetic algorithm, said individuals being selected to control further evolution through evolutionary genetic processing based on user evaluation information. A method according to claim 1, wherein said relation between the amount of the primary output regulation means and that of the secondary regulation means is comprises static and/or dynamic characteristics. A method according to claim 2, wherein said dynamic characteristics include either at least primary delay (T) or differential characteristics (Td). A method according to one of the preceding claims 1 to 3, wherein said user properties include any of at least user preference, skill, or condition. A method according to claim 4, wherein a determination of said user preference is carried out based on a length of time in which the user manipulates an input device for inputting the user evaluation information. A method according to one of the preceding claims 1 to 5, wherein a device actuates the secondary output regulation means on the basis of the amount of manipulation of the primary output regulation means. A method according to one of the preceding claims 1 to 6, wherein said power source is an internal combustion engine, the primary output regulation means is any of an acceleration pedal, acceleration grip, or acceleration lever, the secondary output regulation means is a throttle valve, and said device for actuating the secondary output regulation means is a stepping motor for driving said throttle valve. A method according to one of the preceding claims 1 to 6, wherein said power source is an electric motor, the primary output regulation means is any of an acceleration pedal, acceleration grip, or acceleration lever, and said device for actuating the secondary output regulation means is a control device for performing energization control on the electric motor. Control apparatus for controlling an output of a power source of a vehicle, comprising: means for determining an amount of manipulation of a secondary output regulation means for directly regulating the output of the power source based on an amount of manipulation of a primary output regulation means manipulatable by a user, means for evolutionally altering a relation between the amount of manipulation of the primary output regulation means and of the secondary output regulation means, a control unit adapted to change the relation between the amount of manipulation of the primary output regulation means and of the secondary output regulation means based on any of at least user properties, driving conditions, change of driving environment, or deterioration of the power source over time, characterised in that said control unit is adapted to evolutionary altering the relation between the amount of manipulation of the primary and secondary output regulation means by generating individuals through evolutional processing using a genetic algorithm, said individuals being selected to control further evolution through evolutionary genetic processing based on user evaluation information, and by an evaluation value input device for inputting an evaluation value by the user for affecting the control unit, means for evolutionally altering a relation between the amount of manipulation of the primary output regulation means and of the secondary output regulation means, a control unit adapted to change the relation between the amount of manipulation of the primary output regulation means and of the secondary output regulation means based on any of at least user properties, driving conditions, change of driving environment, or deterioration of the power source over time. Control apparatus according to claim 9, wherein the control unit operates with static and/or dynamic characteristics between the primary and secondary output regulation means. Control apparatus according to claims 9 or 10 wherein said evaluation value input device is adapted to determine the user preference based on a length of time in which the user operates said input device. Control apparatus according to one of the preceding claims 9 to 11, wherein a device is provided for actuating the secondary output regulation means on the basis of the amount of manipulation of the primary output regulation means. Control apparatus according to one of the claims 9 to 12, wherein said power source is an internal combustion engine, the primary output regulation means is any of an acceleration pedal, acceleration grip, or acceleration lever, the secondary output regulation means is a throttle valve, and said device for actuating the secondary output regulation means is a stepping motor for driving said throttle valve. Control apparatus according to one of the claims 9 to 13, wherein said power source is an electric motor, the primary output regulation means is any of an acceleration pedal, acceleration grip, or acceleration lever, and said device for actuating the secondary output regulation means is a control device for performing energization control on the electric motor.

Inventors: KAMIHIRA ICHIKAI, TAKECHI HIROAKI, YAMAGUCHI MASASHI, KAMIHIRA, ICHIKAI, TAKECHI, HIROAKI, YAMAGUCHI, MASASHI
Applicants: YAMAHA MOTOR CO LTD, YAMAHA HATSUDOKI KABUSHIKI KAISHA
Application year: 1999
Main classification: F02D11
IPC codes: F02D11, F02D41, G05B13, F02D45, F02D9