Run curve generation device and run curve generation method for hybrid railway vehicle

Abstract

The purpose of the present invention is to provide, in a hybrid railway vehicle using a power generation device and an electricity storage device as power sources, a technique capable of reducing fuel consumption while preventing deterioration of the electricity storage device. Thus, a run curve generation device for the hybrid railway vehicle according to the present invention creates a plurality of run curve candidates and determines, from the plurality of run curve candidates, a run curve for the travel of the hybrid railway vehicle, on the basis of at least one electricity storage device deterioration index that affects the deterioration of the electricity storage device and the fuel consumption of the power generation device during traveling. The run curve is selected from among the run curve candidates in which the electricity storage device deterioration index is within a first allowable range, the selected run curve having small fuel consumption. The first allowable range is changed according to the temperature or deterioration state of the electricity storage device.

Description

Ranking Curve Generation Device and Method for Hybrid Railway Vehicles

[0001] The present invention relates to a ranking curve generation device and method for hybrid railway vehicles.

[0002] During railway operation on non-electrified lines, in order to reduce CO ２ emissions, hybrid drive railway vehicles (hereinafter referred to as hybrid railway vehicles), which combine a power generation device using a diesel engine or a fuel cell as a power source and a power storage device such as a lithium-ion battery, have been introduced.

[0003] As a control technology for power sources in hybrid railway vehicles, Patent Document 1 discloses a technique for driving a vehicle without charging from an engine to a power storage device by setting the engine output to be less than or equal to the energy required for driving a motor, or by controlling the engine output so that the engine output is consumed by all devices other than the power storage device.

[0004] Japanese Patent Application Laid-Open No. 2010-132154

[0005] Since the main purpose of combining the power generation device and the power storage device is to reduce fuel consumption, in hybrid railway vehicles, control for reducing fuel consumption is emphasized. However, from the perspective of life cycle cost, it is desirable to also consider suppressing the deterioration of the power storage device. Generally, for cost and man-hour reduction, it is assumed that the replacement of the power storage device is carried out in conjunction with inspections involving large-scale disassembly such as general inspections. However, when the deterioration of the power storage device progresses faster than expected, it may be necessary to replace the power storage device before the general inspection, and measures to deal with such situations are required.

[0006] Patent Document 1 discloses a technique for driving a vehicle without charging from an engine to a power storage device by controlling the output of the engine. However, there is no description or suggestion regarding the prevention of deterioration of the power storage device in hybrid railway vehicles, and there is a possibility that the deterioration of the power storage device cannot be sufficiently prevented.

[0007] Hybrid railway vehicles are often equipped with small power generators that rely on assistance from energy storage devices. As a result, when powering at maximum notch, even with maximum power generation, the power required for powering is insufficient, and the discharge power of the energy storage device increases. If this situation is left unchecked, it becomes impossible to limit the sum of the absolute values ​​of charging energy and the absolute values ​​of discharging energy, or to prevent the rise in temperature of the energy storage device by reducing charge and discharge losses. Consequently, the deterioration of the energy storage device may not be kept within expectations.

[0008] Therefore, the present invention aims to provide a technology for a hybrid railway vehicle powered by a power generator and an energy storage device that reduces the fuel consumption of the power generator while preventing the deterioration of the energy storage device.

[0009] One representative run curve generation device for a hybrid railway vehicle according to the present invention, which solves the problem, is characterized by creating a plurality of run curve candidates and determining the run curve on which the hybrid railway vehicle will run based on at least one energy storage device degradation index that affects the degradation of the energy storage device and the fuel consumption of the power generation device during operation.

[0010] According to the present invention, in a hybrid railway vehicle powered by a power generator and an energy storage device, it is possible to reduce the fuel consumption of the power generator while preventing deterioration of the energy storage device.

[0011] Figure 1 shows an example of the configuration of the control system for a hybrid railway vehicle in Example 1. Figure 2 shows an example of the processing flow of the run curve generation device in Example 1. Figure 3 shows an example of the adjustment parameters and adjustment pattern list. Figure 4 shows an example of the relationship between the State of Health (SOH) of the energy storage device and the allowable range of the energy storage device degradation index. Figure 5 shows an example of the allowable range of the energy storage device degradation index according to the energy storage device temperature. Figure 6 shows an example of the flow of the timed run curve generation process. Figure 7 shows an example of the generation of the fastest run curve. Figure 8 shows an example of the tensile force characteristics. Figure 9 shows an example of the reference run curve table. Figure 10 shows an example of coasting insertion adjustment and constant speed adjustment. Figure 11 shows an example of the flow for calculating fuel consumption and the energy storage device degradation index. Figure 12 shows an example of a power generation command in the energy management device. Figure 13 shows an example of the simulation results table. Figure 14 shows an example of the configuration of the control system for a hybrid railway vehicle in Example 2. Figure 15 shows an example of the processing flow of the run curve generation device in Example 2. Figure 16 shows an example of the relationship between the voltage maintenance rate during power generation at the rated current of the fuel cell and the allowable range of the fuel cell degradation index. Figure 17 shows an example of the flow for calculating fuel consumption, energy storage device degradation index, and fuel cell degradation index. Figure 18 shows an example of the configuration of the control system for a hybrid railway vehicle in Embodiment 3. Figure 19 shows an example of driver assistance information. Figure 20 shows an example of the main components of the control system for a hybrid railway vehicle in Embodiment 4.

[0012] Embodiments of the present invention will be described below with reference to the drawings. However, the present invention is not limited to these embodiments. Furthermore, in the drawings, identical parts are denoted by the same reference numerals.

[0013] (Example 1) [Configuration of the control system for a hybrid railway vehicle in Example 1] Figure 1 is a diagram showing an example of the configuration of the control system for a hybrid railway vehicle in Example 1. The configuration of the control system in Example 1 will be explained using Figure 1.

[0014] The control system for the hybrid railway vehicle in this embodiment includes a power generator 101, an energy storage device 102, a braking and driving device 103, an auxiliary device 1032, an energy management device 104, a run curve generator 105, and a train control device 106.

[0015] The power generation device 101 generates electricity based on the power generation command information 114 from the energy management device 104 and supplies power to the energy storage device 102, auxiliary equipment 1032, and braking / driving device 103. The power generation device 101 may be an engine power generation system consisting of an engine, a generator, and a converter, or it may be a fuel cell; it can take any form as long as it is a power device capable of generating electricity based on the power generation command from the energy management device 104.

[0016] The energy storage device 102 is electrically connected to the power generator 101, the brake / drive unit 103, and the auxiliary unit 1032. If the power generated by the power generator 101 exceeds the combined power consumption of the brake / drive unit 103 and the auxiliary unit 1032, the difference is charged. If the power generated by the power generator 101 falls below the combined power consumption of the brake / drive unit 103 and the auxiliary unit 1032, the difference is discharged. The energy storage device 102 outputs SOC (State of Charge) information 1121 to the energy management device 104. The energy storage device 102 also outputs energy storage device status information 1122, which includes SOC, temperature, and SOH (State of Health), to the run curve generation device 105. The energy storage device 102 can be any rechargeable battery device, such as a lithium-ion battery or a nickel-metal hydride battery.

[0017] The braking and driving unit 103 receives power from the power generator 101 and the energy storage unit 102, and drives the vehicle via the inverter and motor. When the vehicle decelerates, it converts the deceleration energy into electricity via the motor and inverter and discharges it to the power generator 101, auxiliary equipment 1032, and energy storage unit 102. The braking and driving unit 103 determines the traction force and electric braking force based on the notch command information 116 input from the train control device 106.

[0018] The auxiliary unit 1032 receives power from the power generator 101 and the energy storage device 102 to drive equipment such as the air conditioning and lighting inside the vehicle and the onboard computer. The auxiliary unit 1032 outputs the power input to the auxiliary unit as auxiliary unit power information 1132 to the run curve generator 105.

[0019] The energy management device 104 determines the power generated by the power generator 101 so as to maintain the State of Control (SOC) of the energy storage device 102 within a predetermined range, and outputs it as power generation command information 114. The functions of the energy management device 104 will be explained in step 1103, which will be described later.

[0020] The run curve generation device 105 generates a run curve based on the energy storage device status information 1122 input from the energy storage device 102 and the auxiliary equipment power information 1132 input from the auxiliary equipment 1032, and outputs this as run curve information 115 to the train control device 106. Details of the processing of the run curve generation device 105 will be described later.

[0021] The train control device 106 calculates the power notch and deceleration notch to allow the train to run along the run curve based on the run curve information 115 input from the run curve generation device 105, and outputs it to the brake drive device 103 as notch command information 116. Possible methods for notch control along the run curve include, for example, proportional control of the notch according to the difference between the speed on the run curve and the current speed.

[0022] [Overview of the processing of the run curve generation device in Example 1] Figure 2 is a diagram showing an example of the processing flow of the run curve generation device in Example 1. The overview of the processing of the run curve generation device 105 will be explained in accordance with steps 200 to 207 in Figure 2.

[0023] Step 200 is a process to adjust the tolerance range of the energy storage device degradation index, which affects the degradation of the energy storage device. The tolerance range of the energy storage device degradation index is used in step 205, described later, when selecting a control run curve from multiple run curve candidates. In this process, the tolerance range is adjusted based on energy storage device status information 1122 and other information input from the energy storage device 102. Details of this tolerance range adjustment will be explained later in [Step 200 (Adjustment Process for Tolerance Range of Energy Storage Device Degradation Index)].

[0024] Step 201 is the process of creating an adjustment pattern list. Figure 3 shows an example of adjustment parameters and an adjustment pattern list. The adjustment pattern list created in step 201 will be explained using Figure 3.

[0025] Figure 3(a) shows table 301, which illustrates the combination of adjustment parameters and their values. Table 301 provides five types of adjustment parameters, and each parameter can be set to three different values, but this is not the only option.

[0026] Here, the adjustment parameters "Power Notch Upper Limit (50 km / h or above)" and "Power Notch Upper Limit (less than 50 km / h)" refer to the upper limits of the power notch when the speed is 50 km / h or above, or less than 50 km / h, respectively, and the "value" refers to the step of the power notch. Similarly, the adjustment parameters "Deceleration Notch (50 km / h or above)" and "Deceleration Notch Upper Limit (less than 50 km / h)" refer to the upper limits of the deceleration notch when the speed is 50 km / h or above, or less than 50 km / h, respectively, and the "value" refers to the step of the deceleration notch. The adjustment parameter "Constant Speed ​​Driving Correction Coefficient" will be explained later in the section on equipment efficiency.

[0027] In step 201, the combination of values ​​for each adjustment parameter is changed based on table 301 to create adjustment pattern list 302 in Figure 3(b). For example, adjustment pattern 1 in 302 is created using the highest value for each adjustment parameter. The next adjustment pattern 2 is created by changing only P5 to P4 for the "power notch upper limit (50 km / h or higher)" from adjustment pattern 1. This procedure is repeated, and adjustment patterns are created by changing the value of each adjustment parameter one by one in a brute-force manner, thereby completing the adjustment pattern list 302.

[0028] Step 202 is a loop process. This loop process is repeated for the number of columns (number of adjustment patterns) in the adjustment pattern list 302 created in step 201.

[0029] Step 203 is the process of creating a fixed-time running curve. Using the adjustment parameters set in each loop of Step 202, a fixed-time running curve is created that allows for timely travel between the specified stations. Details of the process of creating a fixed-time running curve will be explained later in [Step 203 (Process of Creating a Fixed-Time Running Curve)].

[0030] Step 204 is the process of calculating fuel consumption and the energy storage device degradation index. In this process, a simulation is performed in which the hybrid railway vehicle is run according to the fixed-time run curve created in Step 203, and the fuel consumption and energy storage device degradation index are calculated. Details of the calculation of fuel consumption and the energy storage device degradation index will be explained below in [Step 204 (Calculation process of fuel consumption and energy storage device degradation index)].

[0031] Step 205 is the run curve candidate determination process. In this process, if the energy storage device degradation index calculated in step 204 for the time run curve created in step 203 falls within the allowable range adjusted in step 200, and the fuel consumption calculated in the same step is smaller than the already stored recorded value, then the time run curve is determined to be the latest run curve candidate and the process proceeds to step 206. Otherwise, step 206 is skipped and the loop processing in step 202 is terminated.

[0032] Step 206 is the process of updating the run curve candidates. A regular run curve that satisfies the determination in step 205 is stored as a new run curve candidate, and the fuel consumption calculated in step 204 is stored as a new record value.

[0033] Once the processing in step 206 is complete, the end of the loop processing in step 202 is determined. If the creation of time-based run curves for all columns (all adjustment patterns) in the adjustment pattern list 302 has been completed in the loop processing up to that point, proceed to step 207; otherwise, return to step 202 to set the next adjustment pattern and proceed to step 203.

[0034] Step 207 is the process of outputting run curve information 115. The run curve candidate that was last stored in step 206 is output to the train control device 106 as run curve information 115.

[0035] Steps 200, 203, and 204 will be described in detail below. [Step 200 (Adjustment of the Tolerance Range of the Energy Storage Device Degradation Index)] The details of the adjustment of the tolerance range of the energy storage device degradation index in step 200 will be described below. Measures to prevent the degradation of the energy storage device include preventing excessive temperature rise, optimizing the SOC usage range, and suppressing the amount of charging and discharging. By performing control that takes these into consideration while driving, it is possible to prevent the degradation of the energy storage device. To achieve this, in this embodiment, four factors are set as the energy storage device degradation index: the maximum energy storage device temperature, the root mean square of the charging and discharging current, the average SOC value, and the sum of the absolute value of the charging energy and the absolute value of the discharging energy.

[0036] Ideally, the tolerance range for energy storage device degradation indicators should be set after conducting cycle tests on the energy storage device and considering the expected amount of degradation until the energy storage device is replaced. However, in reality, energy storage devices may be used in ways different from the design assumptions, or there may be errors in the design assumptions, meaning that the tolerance range determined at the time of design may not be sufficient to prevent degradation of the energy storage device. This embodiment attempts to appropriately prevent degradation of the energy storage device in accordance with actual conditions by adjusting the tolerance ranges of the four energy storage device degradation indicators described above according to, for example, the state of health (SOH) and temperature of the energy storage device at the time of run curve generation.

[0037] Figure 4 shows an example of the relationship between the State of Health (SOH) of an energy storage device and the acceptable range of the energy storage device degradation index. The adjustment of the acceptable range of the energy storage device degradation index according to the SOH of the energy storage device will be explained using Figure 4.

[0038] <Degradation of Energy Storage Devices> Figure 4(a), section 401, is a graph showing the relationship between the elapsed time since the installation of the energy storage device and the State of Health (SOH). When designing hybrid railway vehicles, it is assumed that the energy storage device will be replaced in conjunction with inspections involving large-scale disassembly, such as general inspections, and the energy storage device to be installed is determined so that the SOH does not fall below the replacement threshold until the general inspection. In actual operation, if the actual SOH is lower than the assumed SOH, there is a possibility that it will fall below the replacement threshold before the replacement time is reached. Therefore, it is desirable to change the tolerance range of the energy storage device degradation index to narrow in accordance with the difference between the assumed SOH and the actual SOH, and to slow down the progression of degradation so that the subsequent degradation of SOH is as close to the assumed SOH as possible. Conversely, if the actual SOH is higher than the assumed SOH, it is possible to change the tolerance range to widen it, thereby reducing the fuel consumption of the power generation device without increasing the frequency of energy storage device replacement.

[0039] <Adjustment of the Tolerance Range of the Energy Storage Device Degradation Index 1> Figure 4(b) shows table 402, which indicates the tolerance range of the maximum energy storage device temperature according to the difference between the assumed SOH and the actual SOH. In this embodiment, the tolerance range of the maximum energy storage device temperature is adjusted using table 402 based on the difference between the assumed SOH and the actual SOH. For example, if the difference ratio between the actual SOH and the assumed SOH at the time of run curve generation is greater than 1% but less than or equal to 2%, the tolerance range of the maximum energy storage device temperature is adjusted to 48°C or less, and the run curve is generated to satisfy this.

[0040] Figure 4(c) shows table 403, which indicates the allowable range of the average SOC value according to the difference between the assumed SOH and the actual SOH, and Figure 4(d) shows table 404, which indicates the allowable range of the sum of the absolute value of charging energy and the absolute value of discharging energy (absolute value of charge / discharge energy) according to the difference between the assumed SOH and the actual SOH. Similar to the allowable range of the maximum temperature of the energy storage device, the allowable range of the average SOC value is adjusted using table 403, and the allowable range of the sum of the absolute value of charging energy and the absolute value of discharging energy is adjusted using table 404.

[0041] <Adjustment of the Tolerance Range of the Energy Storage Device Degradation Index 2> Figure 5 shows an example of the tolerance range of the energy storage device degradation index according to the energy storage device temperature. The root mean square of the charge / discharge current, which is one of the energy storage device degradation indicators, is a parameter that affects the temperature rise of the energy storage device. The main cause of heat generation in the energy storage device is the heat generated when the charge / discharge current flows through the internal resistance, and the internal resistance loss occurs in proportion to the square of the current. Therefore, the temperature rise of the energy storage device can be prevented by managing the root mean square of the charge / discharge current. For this reason, it is desirable to change the tolerance range of the root mean square of the charge / discharge current according to the current temperature of the energy storage device. For example, if the energy storage device temperature is already high towards the end of operation, frequent charging and discharging during the remaining run may cause the temperature to rise excessively, so it may be considered to change the tolerance range of the root mean square of the charge / discharge current to a smaller value.

[0042] Figure 5, section 501, is a table showing the allowable range of the root mean square of the charge and discharge current according to the temperature of the energy storage device. In this embodiment, the allowable range of the root mean square of the charge and discharge current is adjusted using table 501 based on the temperature of the energy storage device. For example, if the temperature of the energy storage device at the time of run curve generation is between 35°C and 40°C, the allowable range of the root mean square of the charge and discharge current is adjusted to 90A or less, and the run curve is generated to satisfy this.

[0043] [Step 203 (Scheduled Run Curve Creation Process)] The details of the scheduled run curve creation process in Step 203 will be explained. Figure 6 is a diagram showing an example of the flow of the scheduled run curve generation process. The scheduled run curve creation process will be explained according to steps 600 to 606 in Figure 6.

[0044] <Generating the Fastest Run Curve> Figure 7 shows an example of generating the fastest run curve. First, the process of generating the brake pattern in step 600 will be explained using 701 in Figure 7(a).

[0045] The braking pattern is a type of run curve generated by calculating in the opposite direction of travel, starting from the position of the next station, assuming that the train will decelerate at a predetermined deceleration rate and stop at the next station. Speed ​​is calculated using equation (1), and position is calculated using equation (2) or equation (3), and the calculation continues until the speed reaches the speed limit. In this embodiment, uphill and downhill are defined such that the position value increases as the train moves downhill, but for lines where the position value decreases as the train moves downhill, this can be handled by swapping equations (2) and (3). (When the calculation is in the direction of travel and the direction of travel is downhill, or when the calculation is in the opposite direction of travel and the direction of travel is uphill) (When the calculation is in the direction of travel and the direction of travel is uphill, or when the calculation is in the opposite direction of travel and the direction of travel is downhill) (Parameter explanation) V: Speed ​​[km / h] V ｂｆ : Velocity before step 1 [km / h] (initial value is 0 km / h) β: Deceleration [km / h / s] Tp: Run curve calculation period [s] D: Position [km] D Ｂｆ : Position [km] of the previous step (initial value is the destination station position)

[0046] In equation (1), β is the deceleration that changes depending on the deceleration notch. The maximum deceleration notch (B7 at 301 in Figure 3) is used as the basis, but if an upper limit for the deceleration notch is set in the adjustment pattern being set in the loop processing of step 202, the upper limit of the deceleration notch (for example, B6 or B5) is given priority, and the deceleration corresponding to the preferred deceleration notch is used in the calculation.

[0047] Next, the process of generating the fastest run curve as the reference run curve in step 601 will be explained using 702 in Figure 7(b).

[0048] The fastest run curve is a type of run curve generated by calculating the speed in the direction of travel, starting from the departure station, assuming that the train travels at the maximum speed within the speed limit from the departure station to the destination station. The method of calculating the speed in the fastest run curve differs for each scenario: acceleration, constant speed travel, and deceleration, and is calculated using equations (4) to (9), respectively. The position is calculated using equation (2) or (3). The initial state is the departure station position and speed of 0 km / h, and the speed is calculated for each run curve calculation cycle, ending the calculation when the next station is reached.

[0049] Note that the run curve calculation period is a hypothetical time used to calculate the run curve and is unrelated to the actual control period or the passage of time in reality. The switch from powering to constant speed driving occurs when the speed reaches the speed limit. The switch from constant speed driving to deceleration driving occurs when the speed reaches the braking pattern.

[0050] (during power running) Rr=(a+b×V)×M+c×V ２ (5) (When traveling at constant speed) V=V (8) (When decelerating) V=V ｂｆ -β × Tp (9) (Explanation of parameters) V: Velocity [km / h] V ｂｆ: Speed ​​in the previous calculation cycle [km / h] Tf: Tensile force [kN] Rr: Running resistance [kN] Rc: Curve resistance [kN] (Calculated only when the train is traveling on a curve) Rg: Gradient resistance [kN] Rad: Reference curve radius for curve resistance [m] K(D): Curve radius that varies with position [m] (Considering the length of the train, it is desirable to use the value of the smallest curve radius among the curves the train is passing through) Grd(D): Gradient value that varies with position [‰] (Considering the length of the train, it is desirable to use the average value of the gradient value the train is passing through) a: Running resistance coefficient 1 (Coefficient related to rolling resistance, etc.) b: Running resistance coefficient 2 (Coefficient related to frictional resistance between wheels and rails) c: Running resistance coefficient 3 (Coefficient related to air resistance, etc.) Mr: Mass of the train including rotational inertia mass [t] M: Mass of the train [t] Tp: Run curve calculation period [s] β: Deceleration [km / h / s]

[0051] Figure 8 shows an example of tensile force characteristics. In equation (4), Tf is the tensile force which varies with the motor notch and speed, and is obtained from the motor notch and speed using Figure 8.

[0052] When creating the fastest run curve, the maximum power notch (P5 in 301 of Figure 3) is used as the basis. However, if an upper limit for the power notch (for example, P4 or P3 in 301 of Figure 3) is set in the adjustment pattern being set during the loop processing in step 202, the upper limit of the power notch is prioritized. For example, if adjustment pattern 2 shown in 302 of Figure 3 is set, the upper limit of the power notch for "upper limit of power notch (50 km / h or more)" is P4, and the upper limit of the power notch for "less than upper limit of power notch (50 km / h)" is P5. Therefore, when calculating the fastest run curve, the maximum power notch value P5 is used when the speed is less than 50 km / h, and P4 is used when the speed is 50 km / h or more.

[0053] <Storage of Reference Run Curves> Figure 9 shows an example of a reference run curve table. The fastest run curve created in step 601 is stored as a reference run curve in the reference run curve table 901 shown in Figure 9. The information stored includes speed, position, control state, and notch stage for each running time.

[0054] The travel time is entered as the travel time on the line above plus the calculation period used for speed calculation. The speed is entered as the speed calculated by equation (4), equation (8), or equation (9). The position is entered as the value calculated by equation (2) or equation (3). The control state is entered as power if equation (4) was used for speed calculation, constant speed if equation (8) was used, and deceleration if equation (9) was used. The notch is entered as the value of the power notch or deceleration notch assumed when calculating traction force and deceleration.

[0055] Figure 10 shows an example of coasting insertion adjustment and constant speed adjustment. <Creating a coasting insertion adjustment run curve> Step 602 is the process of creating a coasting insertion adjustment run curve. The creation of the coasting insertion adjustment run curve will be explained using 1001 in Figure 10(a).

[0056] Based on the reference run curve created in step 601, the run curve is calculated in the direction of travel, starting from a point where the train has traveled a certain distance back towards the departure station from the deceleration start point or coasting start point, and then coasting is performed. When the coasting section merges with the reference run curve, coasting ends, and the train continues to the next station using the reference run curve. The speed during coasting is calculated using the following formula (10). (Parameter explanation) V: Speed ​​[km / h] V ｂｆ : Speed ​​before the first step [km / h] Rr: Running resistance [kN] (calculated using equation (5)) Rc: Curve resistance [kN] (calculated using equation (6) only when the train is traveling on a curve) Rg: Gradient resistance [kN] (calculated using equation (7)) Mr: Mass of the train including the inertia of the rotating body [t] Tp: Run curve calculation period [s]

[0057] The coasting insertion adjustment run curve calculated in this way is stored in the coasting insertion adjustment run curve table. The format of the coasting insertion adjustment run curve table is the same as the reference run curve table 901, but for the control state, if the formula used for speed calculation is formula (4), powering is entered; if it is formula (8), constant speed is entered; if it is formula (9), deceleration is entered; and if it is formula (10), coasting is entered.

[0058] <Creating a Constant Speed ​​Adjustment Run Curve> Step 603 is the process of creating a constant speed adjustment run curve. The creation of the constant speed adjustment run curve will be explained using 1002 in Figure 10(b).

[0059] Based on the reference run curve created in step 601, the run curve is calculated in the direction of travel, starting from a speed a constant speed lower than the constant speed start speed. Once the constant speed run curve merges with the reference run curve, the constant speed run ends, and the train continues to the next station using the reference run curve. The adjusted constant speed is calculated using equation (8).

[0060] The constant speed adjustment run curve calculated in this way is stored in the constant speed adjustment run curve table. The format of the constant speed adjustment run curve table is the same as that of the reference run curve table 901.

[0061] <Determination of the Standard Run Curve> Step 604 is the process of determining the next standard run curve. The standard run curve is determined by comparing the amount of energy consumed and the amount of travel time increased for the coasting insertion adjustment run curve and the constant speed adjustment run curve. The calculation of the amount of energy consumed and the amount of travel time increased is explained below.

[0062] First, the energy consumption is calculated for each of the following: the standard run curve, the coasting insertion adjustment run curve, and the constant speed adjustment run curve, using equation (11). Note that in the second and subsequent loops of the loop processing in step 202, if the coasting insertion adjustment run curve or the constant speed adjustment run curve from the previous loop is adopted as the next standard run curve, the energy consumption calculation result calculated in step 604 of the previous loop can be used, so it is not always necessary to recalculate the energy consumption of the standard run curve. (When the control state is powered) (When the control state is constant speed and the sum of running resistance, curve resistance, and gradient resistance is positive) (When the control state is constant speed and the sum of running resistance, curve resistance, and gradient resistance is negative) (When the control state is coasting) (When the control state is deceleration) (Explanation of Parameters) E: Consumption Energy [kWh] ENDt: Time taken from start to end of travel on the adjustment rank curve (total travel time) P Ｉｎｖ : Input power of the control drive device [kW] Tf: Tensile force [kN] Bf: Deceleration force [kN] ReBf: Electric braking force [kN] η: Equipment efficiency (during power running and deceleration) η ＣＲ : Equipment efficiency (during constant speed running, calculated by η × constant speed running correction coefficient) V: Speed [km / h] V ｂｆ : Speed before 1 step [km / h] Rr: Running resistance [kN] (calculated by Equation (5)) Rc: Curve resistance [kN] (calculated only when the train is running in a curve section by Equation (6)) Rg: Gradient resistance [kN] (calculated by Equation (7)) Mr: Formation mass including the mass of the rotating body [t] Tp: Rank curve calculation period [s]

[0063] ReBf in Equation (16) is the electric braking force that decelerates the vehicle by the regenerative brake of the motor. The electric braking force changes in value according to the speed, similar to the tensile force characteristics shown in Figure 8.

[0064] Regarding the equipment efficiency, there are two types: the value η used during power running and deceleration, and the value η ＣＲ used during constant speed running. The equipment efficiency during constant speed running is set by multiplying the equipment efficiency η used during power running and deceleration by the constant speed running correction coefficient, which is an adjustment parameter.

[0065] Since the equipment efficiency affects the reduction amount of consumption energy, the constant speed running correction coefficient acts as a parameter to adjust the ease of adoption of the constant speed adjustment rank curve. For example, if a value larger than 1 is set as the constant speed running correction coefficient, the equipment efficiency during constant speed running improves and the reduction amount of consumption energy increases. Therefore, in Step 604, the constant speed adjustment rank curve is more likely to be adopted than the coasting insertion adjustment rank curve. That is, if a value larger than 1 is set as the constant speed running correction coefficient, as a result, it is easier to create a rank curve with a short coasting time and a long constant speed running time. If a value smaller than 1 is set, the opposite result occurs.

[0066] Following the calculation of energy consumption, the travel time is calculated. For each of the following: the standard run curve table 901, the coasting insertion adjustment run curve table, and the constant speed adjustment run curve table, the value of the travel time stored in the last row is obtained as the travel time.

[0067] Next, using the calculated energy consumption and travel time for each run curve, the reduction in energy consumption and increase in travel time for the coasting-adjusted run curve and the constant-speed-adjusted run curve are calculated using equations (18) to (21). dE １ = E ｂａｓｅ -E ｃｏａｓｔ (18) dE ２ = E ｂａｓｅ -E ｃｒｕｉｓｅ (19) dT １ = T ｃｏａｓｔ -T ｂａｓｅ (20) dT ２ = T ｃｒｕｉｓｅ -T ｂａｓｅ (21) (Explanation of parameters) dE １ Energy reduction due to coasting insertion adjustment [kWh] dE ２ Energy reduction due to constant speed adjustment [kWh] dT １ : Increase in travel time due to coasting insertion adjustment [s] dT ２ : Increase in travel time due to constant speed adjustment [s] E ｂａｓｅ : Energy consumption [kWh] of the standard run curve E ｃｏａｓｔ Energy consumption [kWh] of the coasting insertion adjustment run curve E ｃｒｕｉｓｅ Energy consumption [kWh] of the constant speed adjustment run curve T ｂａｓｅ : Travel time [s] on the reference run curve T ｃｏａｓｔ : Coasting insertion adjustment run curve travel time [s] T ｃｒｕｉｓｅ : Travel time [s] of the constant speed adjustment run curve

[0068] From the reduction in energy consumption and the increase in driving time for each, dE １ / dT １ and dE ２ / dT ２The two values ​​are compared, and the adjusted run curve with the larger value, i.e., the one with a smaller increase in travel time and a larger energy reduction, is determined as the next standard run curve. The values ​​in the standard run curve table 901 are replaced with the values ​​in the determined adjusted run curve table.

[0069] <Judgment and Output of Scheduled Run Curve> Step 605 is a judgment process. It is determined whether the travel time of the new reference run curve determined in step 604 exceeds the judgment threshold. If the travel time exceeds the judgment threshold, that is, if it is determined that the arrival is not too early compared to the scheduled time, proceed to step 606. Otherwise, that is, if it is determined that the arrival is too early compared to the scheduled time, proceed to step 602. From the viewpoint of preventing late arrivals, it is desirable to set the judgment threshold to a value of the target travel time minus a few seconds. Note that if the travel time of the new reference run curve exceeds the judgment threshold by a predetermined value or more, it will result in a late arrival, so it is desirable to revert the new reference run curve to the previous reference run curve and proceed to step 606.

[0070] Step 606 is the process of outputting the timed run curve. The values ​​of the reference run curve table 901 that satisfy the judgment in step 605 are obtained as values ​​in the timed run curve table and output as the timed run curve. The format of the timed run curve table is the same as that of the reference run curve table 901.

[0071] [Step 204 (Calculation of Fuel Consumption and Energy Storage Degradation Index)] The details of the calculation process for fuel consumption and energy storage degradation index in Step 204 are described below. In Step 204, fuel consumption and energy storage degradation index are calculated by simulating the behavior of the power generation equipment and energy storage equipment when the hybrid railway vehicle is run according to the fixed-time run curve created in Step 203.

[0072] Figure 11 shows an example of a flow chart for calculating fuel consumption and energy storage device degradation indicators. The calculation process for fuel consumption and energy storage device degradation indicators will be explained according to steps 1101 to 1105 in Figure 11.

[0073] Step 1101 is a loop process. This loop process is repeated for the number of rows in the timed running curve table (the number of running times).

[0074] <Calculation of Input Power of Brake and Drive Device> Step 1102 is the process of calculating the input power of the brake and drive device. Based on the control state stored in the timed run curve table, the calculation is performed using equations (12) to (16). Note that if the input power of the brake and drive device calculated in the process of calculating energy consumption in step 604 above has been stored, it is not necessarily required to recalculate it in step 1102.

[0075] <Calculation of Power Generation and Fuel Consumption Rate> Step 1103 is a process for calculating the behavior of the power generation equipment. Since the power generation equipment in a hybrid railway vehicle generates power based on power generation command information from the energy management device, this process also simulates the calculation of power generation command information in the energy management device.

[0076] Figure 12 shows an example of a power generation command in an energy management device. In Figure 12(a), 1201 is a power generation command information control table that represents power generation command information according to the SOC and control state. Power generation command information is obtained by using the power generation command information control table 1201 based on the SOC calculated in step 1104 described later and the control state stored in the timely run curve table.

[0077] Figure 12(b) below shows a power generation characteristics table 1202 which displays the generated power and fuel consumption rate according to the power generation command information. The generated power and fuel consumption rate are calculated using the power generation characteristics table 1202 based on the power generation command information.

[0078] <Calculation of the behavior of the energy storage device> Step 1104 is the process of calculating the behavior of the energy storage device. Various instantaneous values ​​necessary for calculating the energy storage device degradation index are calculated. The energy storage device temperature is calculated using equation (22), the square of the charge / discharge current is calculated using equation (25), the SOC value is calculated using equations (26) and (27), and the charge / discharge power is calculated using equation (28). (Parameter description) Th Ｂａｔ: Power storage device temperature [℃] Th Ｐｒｅｖ : Energy storage device temperature [°C] before Step 1 (Initial state is the actual energy storage device temperature when the run curve is generated) Th Ａｉｒ : Ambient temperature [°C] (Use the actual ambient temperature used when generating the run curve) P Ｈｅａｔ : Heat output [W] P Ｃｏｏｌ : Cooling heat quantity [W (=J / s)] Tp: Calculation period [s] C: Heat capacity of the energy storage device [J / °C] R: Internal resistance of the energy storage device [Ω] I Ｂａｔ : Absolute value of charge / discharge current [A] L Ｂａｔ Ventilation volume [m³] ３ / s] m: air density [kg / m³] ３ ] c Ａｉｒ Specific heat of air [J / (kg·°C)] (Parameter explanation) I ＲＭＳ : The square of the charge / discharge current [A] ２ ] P Ｂａｔ : Charge / discharge power [kW] (calculated using formula (28)) V Ｂａｔ : Voltage of the energy storage device [V] Tp: Calculation period [s] (SOC calculation formula during charging) (Formula for calculating SOC during discharge) (Parameter explanation) SOC: Remaining charge of energy storage device [%] SOC Ｐｒｅｖ : SOC [%] from the previous step (Initial state is the actual SOC at the time of run curve generation) P Ｂａｔ : Charge / discharge power (discharge is positive) [kW] A: Capacity of the energy storage device [kWh] Tp: Calculation period [s] η Ｂａｔ : Charge and discharge efficiency of energy storage devices [dimensionless number] (Parameter explanation) P Ｂａｔ : Charge / discharge power (discharge is positive) [kW] P Ｒｅｇ : Power generated [kW] (calculated in step 1103) P Ｉｎｖ : Input power of braking / driving device (consumption is positive) [kW] (calculated in step 1102) P ＡＰＳ : Auxiliary equipment input power [kW] (Uses auxiliary equipment power consumption during ramp curve generation)

[0079] Figure 13 shows an example of a simulation results table. 1301 in Figure 13 is the simulation results table 1301, which stores the calculated values. The calculation period, speed, position, control state, and notch values ​​are obtained from the time-run curve table. The fuel consumption rate is obtained from the power generation characteristics table 1202, the energy storage device temperature is calculated using equation (22), the square of the discharge current is calculated using equation (25), the SOC is calculated using equations (26) and (27), and the charge / discharge power is calculated using equation (28).

[0080] Once the processing in step 1104 is complete, the end of the loop processing in step 1101 is determined. If the calculations for all rows (total running time) of the timed running curve table have been completed in the loop processing up to that point, proceed to step 1105. If not, return to step 1101 and proceed again to step 1102 and below to calculate each value for the next running time.

[0081] Step 1105 is a process for calculating fuel consumption and energy storage device degradation index for a fixed-time run curve.

[0082] <Calculation of Fuel Consumption> Fuel consumption is calculated using formula (29). (SOC) Ｅｎｄ <SOC Ｓｔａｒｔ F in this case ΔＳＯＣ ) (SOC) Ｅｎｄ ≥ SOC Ｓｔａｒｔ F in this case ΔＳＯＣ ) (Parameter explanation) F: Fuel consumption [L] F ΔＳＯＣ : Fuel consumption calculated by converting the difference in SOC between the start and end of the journey [L] FL: Fuel consumption rate [L / h] Tp: Calculation period [s] SOC Ｓｔａｒｔ : SOC at the start of driving [%] SOC Ｅｎｄ : SOC [%] at the end of operation A: Capacity of the energy storage device [kWh] η Ｂａｔ : Charge / discharge efficiency of energy storage device [dimensionless number] P Ｃｈａｒｇｅ : Power generation [kW] with ΔSOC correction (using the value for 1N power generation) FL Ｃｈａｒｇｅ : Fuel consumption rate [L / h] with ΔSOC correction (value used for 1N power generation)

[0083] F in equations (29) and (30) ΔＳＯＣ This represents the fuel consumption assuming that the difference in State of Charge (SOC) between the start and end of the journey (ΔSOC) is covered by power generation. If the SOC at the end of the journey is lower than the SOC at the start of the journey, the energy storage device is temporarily taking over the power generation, which may lead to an underestimation of fuel consumption. Therefore, the fuel consumption when ΔSOC is covered by power generation is added to prevent underestimation of fuel consumption. Conversely, if the SOC at the end of the journey is higher, fuel consumption may be overestimated, so ΔSOC is subtracted from the fuel consumption to prevent overestimation.

[0084] <Calculation of Energy Storage Device Degradation Index> The energy storage device degradation index is calculated using equation (32) for the maximum temperature of the energy storage device, equation (33) for the root mean square of the charge / discharge current, equation (34) for the average SOC value, and equation (35) for the sum of the absolute values ​​of the charge energy and the absolute values ​​of the discharge energy. (Parameter description) Th Ｍａｘ : Maximum temperature of the energy storage device [°C] Th ＢａｔＳｔａｒｔ : Energy storage device temperature [°C] (first row of simulation results table 1301) Th ＢａｔＥｎｄ : Energy storage device temperature [°C] (last row of simulation results table 1301) (Parameter explanation) I ＲＭＳＳｕｍ : Root mean square of charge / discharge current [A] ＲＭＳ : The square of the charge / discharge current [A] ２ ] T Ｒｕｎ : Travel time [s] on the scheduled running curve (Parameter description) SOC Ａｖｅ : Average SOC [%] SOC: Remaining energy storage capacity [%] T Ｒｕｎ : Time taken on the regular running curve [s] Tp: Calculation period [s] (Parameter description) E Ｂａｔ : Charge / discharge energy [kWh] P Ｂａｔ : Charge / discharge power (discharge is positive) [kW] Tp: Calculation period [s]

[0085] With the configuration of Embodiment 1 described above, it is possible to generate a run curve that can reduce fuel consumption while preventing deterioration of the energy storage device.

[0086] (Example 2) [Configuration of the control system for the hybrid railway vehicle in Example 2] Figure 14 is a diagram showing an example of the configuration of the control system for the hybrid railway vehicle in Example 2. The configuration of the control system in Example 2 will be explained using Figure 14.

[0087] The control system for the hybrid railway vehicle in this embodiment consists of a power generator 1401, an energy storage device 102, a braking and driving device 103, an auxiliary device 1032, an energy management device 104, a run curve generator 1405, and a train control device 106.

[0088] The power generation device 1401 generates power based on the power generation command information 114 from the energy management device 104 and supplies power to the energy storage device 102, auxiliary equipment 1032, and braking / driving device 103. In this embodiment, the power generation device 1401 is composed of a fuel cell. The power generation device 1401 outputs the degradation state of the fuel cell as fuel cell state information 1411 to the run curve generation device 1405.

[0089] The run curve generator 1405 generates a run curve based on the energy storage device status information 1122 input from the energy storage device 102, the auxiliary equipment power information 1132 input from the auxiliary equipment 1032, the fuel cell status information 1411 input from the power generator 1401, etc., and outputs this as run curve information 115 to the train control device 106. Details of the processing of the run curve generator 1405 will be described later. The other configurations are the same as in Example 1, so the explanation will be omitted.

[0090] [Overview of the processing of the run curve generation device in Example 2] Figure 15 shows an example of the processing flow of the run curve generation device in Example 2. The overview of the processing of the run curve generation device 1405 will be explained in accordance with steps 1500 to 207 in Figure 15.

[0091] Step 1500 is a process to adjust the tolerance range of the energy storage device degradation index and the fuel cell degradation index, which affects the degradation of the fuel cell. Details of this process will be explained later in [Step 1500 (Process to adjust the tolerance range of the energy storage device degradation index and fuel cell degradation index)].

[0092] Since the processes in steps 201, 202, and 203 of Figure 15 are the same as those described in Example 1, their explanation will be omitted.

[0093] Step 1504 is the process of calculating fuel consumption, energy storage device degradation index, and fuel cell degradation index. Details of this process will be explained later in [Step 1504 (Calculation process for fuel consumption, energy storage device degradation index, and fuel cell degradation index)].

[0094] Step 1505 is the run curve candidate determination process. In this process, if the energy storage device degradation index and fuel cell degradation index calculated in step 1504 for the time run curve created in step 203 are within the acceptable range adjusted in step 1500, and the fuel consumption calculated in the same step is smaller than the already stored recorded value, then the time run curve is determined to be the latest run curve candidate and the process proceeds to step 206. Otherwise, step 206 is skipped and the loop processing in step 202 is terminated.

[0095] Since the processes in steps 206 and 207 of Figure 15 are the same as those described in Example 1, their explanation will be omitted.

[0096] [Step 1500 (Adjustment of Tolerance Range for Energy Storage Device Degradation Index and Fuel Cell Degradation Index)] The details of the adjustment of the tolerance range for the fuel cell degradation index in Step 1500 will be explained below. The adjustment of the tolerance range for the energy storage device degradation index is the same as that described in Example 1, so the explanation will be omitted.

[0097] To prevent fuel cell degradation, measures such as reducing the number of load fluctuations (e.g., the number of power generation switching cycles) and improving the power generation time at rated output are known, and by implementing control that takes these into account during operation, it is possible to prevent fuel cell degradation. To achieve this, in this embodiment, two indicators of fuel cell degradation are set: the number of power generation changes and the average power generation.

[0098] Ideally, the tolerance range for fuel cell degradation indicators should be set after conducting fuel cell cycle tests and considering the expected amount of degradation until the fuel cell replacement time. However, in reality, fuel cells may be used in operations different from those assumed during the design phase, or there may be errors in the design assumptions, meaning that the tolerance range determined during the design phase may not be sufficient to prevent fuel cell degradation. This embodiment aims to appropriately prevent fuel cell degradation in accordance with actual conditions by adjusting the tolerance range of the fuel cell degradation indicator according to the degradation state of the fuel cell, as indicated by, for example, the voltage maintenance rate during power generation at the rated current.

[0099] Figure 16 shows an example of the relationship between the voltage maintenance rate during power generation at the rated current of the fuel cell and the allowable range of the fuel cell degradation index. The adjustment of the allowable range of the fuel cell degradation index according to the degradation state during power generation at the rated current of the fuel cell will be explained using Figure 16.

[0100] <Fuel Cell Degradation> Figure 16, section 1601, is a graph showing the relationship between the elapsed time since fuel cell installation and the assumed degradation state. When designing hybrid railway vehicles, it is assumed that fuel cells will be replaced in conjunction with inspections involving large-scale disassembly, such as general inspections, and the fuel cells to be installed are determined so that the voltage maintenance rate during rated current generation does not fall below the replacement threshold until the general inspection. In actual operation, if the actual voltage maintenance rate is lower than the assumed voltage maintenance rate, there is a possibility that it will fall below the replacement threshold before the replacement time is reached. Therefore, it is desirable to narrow the allowable range of the fuel cell degradation index in accordance with the difference between the actual voltage maintenance rate and the assumed voltage maintenance rate, and to slow down the progression of degradation so that the subsequent changes in the degradation state are as close as possible to the assumed degradation state.

[0101] <Adjustment of the Tolerance Range of Fuel Cell Degradation Indicators> Figure 1602 is a table showing the tolerance range for the number of power generation switching cycles according to the difference between the assumed voltage maintenance rate and the actual voltage maintenance rate when generating at rated current. In this embodiment, the tolerance range for the number of power generation switching cycles is adjusted using table 1602 based on the difference between the assumed voltage maintenance rate and the actual voltage maintenance rate. For example, if the difference ratio between the actual voltage maintenance rate and the assumed voltage maintenance rate at the time of run curve generation is greater than 1% but less than or equal to 2%, the tolerance range for the number of power generation switching cycles is adjusted to 7 or less, and the run curve is generated to satisfy this.

[0102] Table 1603 in Figure 16 shows the allowable range of average generated power according to the difference between the assumed voltage maintenance rate and the actual voltage maintenance rate. Similar to the allowable range for the number of power generation switching cycles, the allowable range for average generated power is adjusted using table 1603.

[0103] [Step 1504 (Calculation process for fuel consumption, energy storage device degradation index, and fuel cell degradation index)] The calculation process for fuel consumption, energy storage device degradation index, and fuel cell degradation index in Step 1504 will be explained below.

[0104] Figure 17 shows an example of a flow chart for calculating fuel consumption, energy storage device degradation index, and fuel cell degradation index. The calculation process for fuel consumption, energy storage device degradation index, and fuel cell degradation index is carried out according to steps 1101 to 1705 in Figure 17, but the processing of steps 1101, 1102, 1103, and 1104 is the same as that described in Example 1, so the explanation is omitted.

[0105] Step 1705 is the process of calculating fuel consumption, energy storage device degradation index, and fuel cell degradation index for a fixed-time run curve. The process of calculating fuel consumption and energy storage device degradation index is the same as in Example 1, so the explanation will be omitted, and only the calculation of the fuel cell degradation index will be explained.

[0106] <Calculation of Fuel Cell Degradation Index> The number of changes in power generation, one of the fuel cell degradation indexes, is calculated by looking at the power generation from the beginning in the simulation results table shown in 1301 of Figure 13, and counting up each time the power generation changes to a different value.

[0107] The average power generation index, one of the fuel cell degradation indicators, is calculated using formula (36). (Parameter explanation) P Ａｖｅ : Average value of generated power [kW] P Ｒｅｇ Power generation [kW] T Ｒｕｎ : Time taken on the regular running curve [s] Tp: Calculation period [s]

[0108] With the configuration of Embodiment 2 described above, it is possible to generate a run curve that can reduce fuel consumption while preventing deterioration of both the energy storage device and the fuel cell.

[0109] In this embodiment, as a measure to prevent fuel cell degradation, the allowable range of average power generation was used for control in order to improve the proportion of power generation at rated output. However, it is also conceivable to calculate the proportion of power generation time at rated output to the total power generation time and select a run curve in which that proportion falls within a predetermined allowable range as a candidate for an energy-saving run curve.

[0110] (Example 3) [Configuration of the control system for the hybrid railway vehicle in Example 3] Figure 18 is a diagram showing an example of the configuration of the control system for the hybrid railway vehicle in Example 3. The configuration of the control system in Example 3 will be explained using Figure 18.

[0111] The control system for the hybrid railway vehicle in this embodiment consists of a power generator 101, an energy storage device 102, a braking and driving device 103, an auxiliary device 1032, an energy management device 104, a run curve generation device 105, and a driver support information display device 1807.

[0112] The braking and driving system 103 receives power from the generator 101 and the energy storage device 102, and drives the vehicle via the inverter and motor. When the vehicle decelerates, it converts the deceleration energy into electricity via the motor and inverter and discharges it to the generator 101, auxiliary equipment 1032, and energy storage device 102. The braking and driving system determines the traction force and electric braking force based on the driver's operating notch.

[0113] <Driving Support Information Display Device> The driving support information display device 1807 displays the run curve information 115 input from the run curve generation device 105 as support information to the driver of the hybrid railway vehicle. Both real-time display during operation and display before the start of operation are possible methods of display.

[0114] Figure 19 shows an example of driver assistance information. Figure 19(a), 1901, is an example of the presentation of real-time driver assistance information while driving. Real-time driver assistance information can include the number of stages of the power notch and deceleration notch, the next operation, the speed at which the next operation is switched, and the distance to the position where the next operation is switched. The number of stages of the power notch and deceleration notch can be presented by referring to the run curve information 115 at the current driving position and obtaining the notch information. The next operation can be presented by searching the run curve information 115 in the direction of the next station from the current driving position, finding the point at which the notch or control state at the current driving position switches to a different notch or control state, and obtaining the notch or control state at that point. The speed at which the next operation is switched can be presented by obtaining the speed at the aforementioned switching point, and the distance to switch to the next operation can also be presented by calculating the difference between the aforementioned switching point and the current driving position. In example 1901, we showed an example of displaying text information, but it is also acceptable to use graphics, sound, etc., to represent it.

[0115] Figure 19(b), item 1902, shows an example of the presentation of driver assistance information before starting to travel. The driver assistance information before starting to travel can be presented in the form of a speed profile, plotting the run curve to the next station with position on the horizontal axis and speed on the vertical axis. In addition, by presenting information on the number of power notch stages, control status, and switching timing next to the speed profile, it is thought that it will become easier to understand what kind of operation to perform at what timing to achieve both reduced fuel consumption and prevention of deterioration of the energy storage device. The other configurations are the same as in Embodiment 1, so the explanation will be omitted.

[0116] With the configuration of Embodiment 3 described above, the driver can operate the hybrid railway vehicle according to the run curve, which is expected to reduce fuel consumption while preventing deterioration of the energy storage device.

[0117] (Example 4) [Key parts of the control system for the hybrid railway vehicle in Example 4] Figure 20 shows an example of the key parts of the control system for the hybrid railway vehicle in Example 4. The key parts of the control system in Example 4 will be explained using Figure 20.

[0118] The control system for the hybrid railway vehicle in this embodiment includes a run curve generation device 2005, a condition input IF 2001 for exchanging control information, and a run curve presentation device 2007. The other configurations are the same as in Embodiment 1, and therefore will not be described further.

[0119] <Condition Input IF> The Condition Input IF 2001 acquires information about the distance between stations to be included in the run curve generation, as well as information about the conditions necessary for run curve generation, such as the SOH and temperature of the energy storage device, using the HMI (Human Machine Interface), and outputs it as input condition information 2011.

[0120] The run curve generation device 2005 receives input condition information 2011 from the condition input IF 2001, generates a run curve, and outputs run curve information 115 to the run curve presentation device 2007. Since the configuration is the same as in Example 1, except that the conditions necessary for run curve generation are input from the condition input IF 2001, a detailed explanation is omitted.

[0121] The run curve display device 2007 receives run curve information 115 from the run curve generation device 2005 and displays the run curve information to the user. The content to be displayed is the same as the content of the support information displayed before the start of driving as described in Example 3, so the explanation is omitted.

[0122] With the configuration of Embodiment 4 described above, it becomes possible to use a run curve that can reduce fuel consumption while preventing deterioration of the energy storage device for driver training and other purposes.

[0123] (Supplementary Information) The present invention is not limited to the embodiments described above, and includes various modifications that do not depart from the spirit of the invention. For example, the present invention is not limited to having all the configurations described in the embodiments described above, but also includes configurations in which some of the configurations are omitted. Furthermore, it is possible to add or replace a part of the configuration of one embodiment with a configuration of another embodiment. Several modifications are listed below.

[0124] In Example 1, the State of Health (SOH) and temperature of the energy storage device were used to measure the degradation state of the energy storage device, but these are not the only methods. Any method that correlates with the degradation state of the energy storage device can be used.

[0125] In Example 1, four indicators were set as energy storage device degradation indicators: the maximum temperature of the energy storage device, the root mean square of the charge / discharge current, the average SOC value, and the sum of the absolute values ​​of the charge energy and the absolute values ​​of the discharge energy. However, these are not the only indicators that can be used. Any of the four indicators may be set. Furthermore, any parameter that affects the degradation of the energy storage device can be adopted as an indicator.

[0126] In Example 1, five types of adjustment parameters were provided: upper limit of power notch (50 km / h or higher), upper limit of power notch (less than 50 km / h), upper limit of deceleration notch (50 km / h or higher), upper limit of deceleration notch (less than 50 km / h), and constant speed correction coefficient. For each of these, three values ​​were available: P5, P4, and P3 for the upper limit of power notch; B7, B6, and B5 for the upper limit of deceleration notch; and 1.2, 1.0, and 0.8 for the constant speed correction coefficient. However, these are not the only possible values. The values ​​for each adjustment parameter can be selected as appropriate. Furthermore, any adjustment parameter that is relevant to the operation of a hybrid railway vehicle can be used.

[0127] In Example 2, the voltage maintenance rate during power generation at the rated current was used to measure the degradation state of the fuel cell, but this is not the only method that can be used. Any method that correlates with the degradation state of the fuel cell can be adopted.

[0128] In Example 2, two indicators were set as fuel cell degradation indicators: the number of power generation changes and the average power generation. However, these are not the only indicators. Either of the two indicators may be set. Alternatively, instead of the average power generation, the ratio of power generation time at rated output to total power generation time may be set. Any parameter that affects fuel cell degradation can be used as an indicator.

[0129] In Example 3, two methods of presenting driving assistance information were shown: a real-time presentation method 1901 during driving and a presentation method 1902 before driving began. However, both methods may be used in combination, and both 1901 and 1902 may be presented on the driving assistance information display device even while driving. Furthermore, any driving assistance information related to the run curve can be presented. The same applies to the run curve information presented by the run curve display device in Example 4.

[0130] In Examples 3 and 4, a train control device is not provided as in Example 1, but a train control device may be provided together with the driver assistance information display device.

[0131] 101, 1401: Power generation device, 102: Energy storage device, 103: Brake and drive device, 1032: Auxiliary equipment, 104: Energy management device, 105, 1405, 2005: Run curve generation device, 106: Train control device, 1121: SOC information, 1122: Energy storage device status information, 1132: Auxiliary equipment power information, 114: Power generation command information, 115: Run curve information, 116: Notch command information, 1411: Fuel cell status information, 1807: Driving support information display device, 2001: Condition input IF, 2007: Run curve display device, 2011: Input condition information

Claims

1. A run curve generation device for a hybrid railway vehicle that runs using a power generator and an energy storage device as power sources, characterized in that it creates a plurality of run curve candidates, and determines the run curve on which the hybrid railway vehicle will run based on at least one energy storage device degradation index that affects the degradation of the energy storage device and the fuel consumption of the power generator during operation from the plurality of run curve candidates.

2. A run curve generation device for a hybrid railway vehicle according to claim 1, characterized in that the device calculates the energy storage device degradation index for the run curve candidates, and among the run curve candidates in which the energy storage device degradation index is within a first allowable range, the run curve with the smallest fuel consumption is determined to be the run curve on which the hybrid railway vehicle will travel.

3. A run curve generation device for a hybrid railway vehicle according to claim 2, characterized in that the first allowable range of the energy storage device degradation index is changed according to the temperature or degradation state of the energy storage device.

4. A run curve generation device for a hybrid railway vehicle according to any one of claims 1 to 3, characterized in that a plurality of run curve candidates are created by changing a combination of conditions for one or more adjustment parameters that affect the run curve.

5. A run curve generation device for a hybrid railway vehicle according to claim 4, wherein the adjustment parameters include a power notch and a deceleration notch, and each can be set to different conditions according to the speed of the hybrid railway vehicle.

6. A run curve generating device for a hybrid railway vehicle according to any one of claims 1 to 5, wherein the energy storage device degradation index includes one of the following: the maximum temperature of the energy storage device, the root mean square of the charge / discharge current, the average SOC value, or the sum of the absolute value of the charge energy and the absolute value of the discharge energy.

7. A run curve generation device for a hybrid railway vehicle according to any one of claims 2 to 6, characterized in that, in addition to calculating a power storage device degradation index for the run curve candidate, at least one power generation device degradation index that affects the degradation of the power generation device is calculated, and among the run curve candidates in which the power storage device degradation index and the power generation device degradation index are within a first allowable range and a second allowable range, respectively, the run curve with the smallest fuel consumption is determined as the run curve on which the hybrid railway vehicle will travel.

8. A run curve generation device for a hybrid railway vehicle according to claim 7, characterized in that the power generation device degradation index includes one of the number of load fluctuations or the average power generation.

9. A run curve generating device for a hybrid railway vehicle according to claim 7 or 8, characterized in that a first allowable range of the degradation index of the energy storage device is changed according to the temperature and degradation state of the energy storage device, and a second allowable range of the degradation index of the power generation device is changed according to the degradation state of the power generation device.

10. A run curve generation device for a hybrid railway vehicle according to any one of claims 1 to 9, characterized in that it outputs driving support information to assist the driver of the hybrid railway vehicle based on the run curve over which the hybrid railway vehicle travels.

11. A run curve generation device for a hybrid railway vehicle according to any one of claims 1 to 10, characterized in that the temperature and degradation state of the energy storage device and the degradation state of the power generation device are input via a human-machine interface.

12. A hybrid railway vehicle equipped with a run curve generating device for a hybrid railway vehicle according to any one of claims 1 to 11.

13. A method for generating a run curve for a hybrid railway vehicle that runs using a power generator and an energy storage device as power sources, characterized by creating a plurality of run curve candidates, and determining the run curve on which the hybrid railway vehicle will run based on at least one energy storage device degradation index that affects the degradation of the energy storage device and the fuel consumption of the power generator during operation, from the plurality of run curve candidates.

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