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

Abstract

The present invention provides a technology that can reduce fuel consumption while preventing deterioration of the energy storage device in a hybrid railway vehicle powered by a power generation device and an energy storage device. [Solution] The hybrid railway vehicle run curve generation device of the present invention 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 generation device during operation. The run curve is the run curve with the smallest fuel consumption among the run curve candidates in which the energy storage device degradation index is within a first allowable range. Furthermore, the first allowable range is changed according to the temperature or degradation state of the energy storage device.

Description

Technical Field

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

Background Art

[0002] In order to reduce the CO2 emissions during railway operation on non-electrified lines, hybrid-driven 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 the power source in a hybrid railway vehicle, Patent Document 1 discloses a technique for driving a vehicle without charging from an engine to a power storage device by making the engine output 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.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[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, but from the perspective of the life cycle cost, it is also desirable to consider suppressing the deterioration of the power storage device. Generally, to reduce costs and labor, the replacement of energy storage devices is expected to be carried out in conjunction with inspections involving large-scale disassembly, such as general inspections. However, if the deterioration of energy storage devices progresses faster than expected, it may become necessary to replace them before the general inspection, and there is a need to address this situation.

[0006] Patent Document 1 discloses a technology for driving a vehicle without charging the energy storage device from the engine by controlling the engine's output. However, it does not describe or suggest how to prevent the deterioration of the energy storage device in hybrid railway vehicles, and there is a possibility that the deterioration of the energy storage device cannot be adequately 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. [Means for solving the problem]

[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 multiple 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. [Effects of the Invention]

[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. [Brief explanation of the drawing]

[0011] [Figure 1] Figure 1 shows an example of the configuration of the control system for a hybrid railway vehicle in Example 1. [Figure 2] Figure 2 shows an example of the processing flow of the run curve generation device in Example 1. [Figure 3] Figure 3 shows an example of adjustment parameters and adjustment pattern lists. [Figure 4] 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. [Figure 5] Figure 5 shows an example of the acceptable range for the degradation index of an energy storage device according to the temperature of the energy storage device. [Figure 6] Figure 6 shows an example of the flow of the timed run curve generation process. [Figure 7] Figure 7 shows an example of generating the fastest run curve. [Figure 8] Figure 8 shows an example of tensile force characteristics. [Figure 9] Figure 9 shows an example of a standard run curve table. [Figure 10] Figure 10 shows an example of coasting insertion adjustment and constant speed adjustment. [Figure 11] Figure 11 shows an example of a flow chart for calculating fuel consumption and energy storage device degradation indicators. [Figure 12] Figure 12 shows an example of a power generation command in an energy management device. [Figure 13] Figure 13 shows an example of a simulation results table. [Figure 14] Figure 14 shows an example of the configuration of the control system for a hybrid railway vehicle in Example 2. [Figure 15]Figure 15 shows an example of the processing flow of the run curve generation device in Example 2. [Figure 16] 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] Figure 17 shows an example of a flow chart for calculating fuel consumption, energy storage device degradation index, and fuel cell degradation index. [Figure 18] Figure 18 shows an example of the configuration of the control system for a hybrid railway vehicle in Example 3. [Figure 19] Figure 19 shows an example of driver assistance information. [Figure 20] Figure 20 shows an example of the main components of the control system for a hybrid railway vehicle in Embodiment 4. [Modes for carrying out the invention]

[0012] Embodiments of the present invention will be described below with reference to the drawings. However, the present invention is not limited by this embodiment. In addition, the same parts are denoted by the same reference numerals in the drawings. [Examples]

[0013] (Example 1) [Configuration of the control system for the hybrid railway vehicle in Example 1] Figure 1 shows 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 with reference to 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 is less than 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 nickel-metal hydride battery.

[0017] The braking and driving unit 103 receives power from the 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 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 equipment 1032 receives power from the generator 101 and the energy storage device 102 to power the in-vehicle air conditioning, lighting, onboard computer, and other equipment. The auxiliary device 1032 outputs the power input to the auxiliary device as auxiliary power information 1132 to the run curve generator 105.

[0019] The energy management device 104 determines the power generated by the power generator 101 to maintain the State of Charge (SOC) of the energy storage device 102 within a predetermined range, and outputs this 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 generator 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 generator 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 apparatus in Example 1] Figure 2 shows an example of the processing flow of the run curve generation device in Example 1. The processing overview of the run curve generator 105 will be explained according to 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 the energy storage device status information 1122 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 the adjustment pattern list. Figure 3 shows an example of adjustment parameters and adjustment pattern lists. The adjustment pattern list created in step 201 will be explained using Figure 3.

[0025] Figure 3(a) shows table 301, which illustrates the combinations 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 "Maximum power notch (50 km / h or above)" and "Maximum power notch (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 power notch level. Similarly, the adjustment parameters "deceleration notch (above 50 km / h)" and "deceleration notch upper limit (below 50 km / h)" refer to the upper limits of the deceleration notch when the speed is above 50 km / h or below 50 km / h, respectively, and the "value" refers to the deceleration notch level. Furthermore, the "constant speed driving correction coefficient" among the adjustment parameters 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, 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 fixed-time running curve creation process will be explained later in [Step 203 (Fixed-Time Running Curve Creation Process)].

[0030] Step 204 is the process of calculating fuel consumption and the energy storage 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 degradation index are calculated. Details of the calculation of fuel consumption and the energy storage degradation index will be explained below in [Step 204 (Calculation Process for Fuel Consumption and Energy Storage 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 criteria of 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, 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 are described in detail below. [Step 200 (Adjustment process for the tolerance range of the energy storage device degradation index)] This section describes the details of the adjustment process for the tolerance range of the energy storage device degradation index in step 200. Known measures to prevent the deterioration of energy storage devices include preventing excessive temperature rise, optimizing the SOC usage range, and suppressing the amount of charging and discharging. By implementing control that takes these factors into consideration while driving, it is possible to prevent the deterioration of energy storage devices. To achieve this, in this embodiment, four indicators of energy storage device deterioration are set: the maximum temperature of the energy storage device, the root mean square of the charging and discharging current, the average SOC value, and the sum of the absolute values ​​of the charging energy and the absolute values ​​of the discharging energy.

[0036] Ideally, the tolerance range for the degradation index of energy storage devices should be set after conducting cycle tests on the energy storage devices and considering the expected amount of degradation until the energy storage device is replaced. However, in reality, due to being used in ways different from the assumptions made during the design phase, or due to errors in the design assumptions, the tolerance range determined during the design phase may not be sufficient to prevent the degradation of the energy storage device. This embodiment aims to appropriately prevent the deterioration of the energy storage device in accordance with actual conditions by adjusting the tolerance range of the four energy storage device degradation indicators mentioned above, for example, according to the 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. Figure 4 illustrates the adjustment of the acceptable range for the energy storage device degradation index according to the State of Health (SOH) of the energy storage device.

[0038] <Deterioration 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 devices will be replaced in conjunction with inspections involving large-scale disassembly, such as general inspections. The energy storage devices to be installed are determined so that the State of Health (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 correspond to the difference between the assumed SOH and the actual SOH, thereby slowing down the progression of degradation so that the subsequent SOH degradation 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 generator without increasing the frequency of energy storage device replacements.

[0039] <Adjustment of the acceptable range for energy storage device degradation indicators 1> Figure 4(b) shows table 402, which indicates the allowable range of the maximum temperature of the energy storage device according to the difference between the assumed SOH and the actual SOH. In this embodiment, the allowable range of the maximum temperature of the energy storage device 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 allowable range of the maximum temperature of the energy storage device is adjusted to 48°C or less, and the run curve is generated to satisfy this.

[0040] Table 403 in Figure 4(c) shows the allowable range of the average SOC value according to the difference between the assumed SOH and the actual SOH, and table 404 in Figure 4(d) shows the allowable range of the sum of the absolute values ​​of charging energy and the absolute values ​​of discharging energy (absolute values ​​of charge and 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 values ​​of charging energy and the absolute values ​​of discharging energy is adjusted using table 404.

[0041] <Adjustment of the acceptable range for energy storage device degradation indicators 2> Figure 5 shows an example of the acceptable range for the degradation index of an energy storage device according to the temperature of the energy storage device. The root mean square of the charge / discharge current, one of the indicators of energy storage device degradation, is a parameter that affects the temperature rise of the energy storage device. The main cause of heat generation in energy storage devices 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. Accordingly, it is desirable to change the allowable range of the root mean square of the charge / discharge current depending on 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 advisable to change the allowable 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 energy storage device temperature. 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 energy storage device temperature. For example, if the energy storage device temperature 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)] Step 203 details the process for creating a regular run curve. Figure 6 shows an example of the flow of the timed run curve generation process. The process for creating a regular run curve 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).

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[0046] In equation (1), β is the deceleration that changes depending on the deceleration notch. The maximum deceleration notch (B7 in 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)

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[0051] Figure 8 shows an example of tensile force characteristics. In equation (4), Tf is the tensile force which varies with the power notch and speed, and is obtained from the power 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 will take precedence. 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 the reference run curve> Figure 9 shows an example of a standard 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 status, 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 or coasting start point, and then coasting is performed. Once the coasting phase 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).

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[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 standard run curve table 901.

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

[0062] First, the energy consumption is calculated for each of the following: the reference 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 reference 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 reference run curve.

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[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 FIG. 8.

[0064] Regarding the machine 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 machine efficiency during constant speed running is set by multiplying the machine efficiency η used during power running and deceleration by the constant speed running correction coefficient, which is an adjustment parameter.

[0065] Since the machine efficiency affects the reduction amount of energy consumption, the constant speed running correction coefficient acts as a parameter for adjusting the ease of adoption of the constant speed adjustment rank curve. For example, if a value greater than 1 is set as the constant speed running correction coefficient, the machine efficiency during constant speed running improves and the reduction amount of energy consumption 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 greater than 1 is set as the constant speed running correction coefficient, as a result, a rank curve with a short coasting time and a long constant speed running time is likely to be created, and if a value less 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). dE1=E base -E coast (18) dE2=E base -E cruise (19) dT1=T coast -T base (20) dT2=T cruise -T base (twenty one) (Parameter description) dE1: Energy reduction due to coasting insertion adjustment [kWh] dE2: Energy savings due to constant speed adjustment [kWh] dT1: Increase in travel time due to coasting insertion adjustment [s] dT2: 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] Based on the reduction in energy consumption and increase in travel time for each system, dE1 / dT1 and dE2 / dT2 are compared, and the adjusted run curve with the larger value—that is, the one with a smaller increase in travel time and a larger energy reduction—is determined as the next baseline run curve. The values ​​in baseline run curve table 901 are replaced with the values ​​in the determined adjusted run curve table.

[0069] <Determination and output of the regular run curve> Step 605 is a judgment process. It determines 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, i.e., if it is determined that the arrival is not too early compared to the scheduled time, proceed to step 606. Otherwise, i.e., if it is determined that the arrival is too early compared to the scheduled time, proceed to step 602. From the perspective 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 process for fuel consumption and energy storage device degradation indicators)] Step 204 details the calculation process for fuel consumption and energy storage device degradation indicators. In step 204, the behavior of the power generation and energy storage systems is simulated when the hybrid railway vehicle is run according to the fixed-run curve created in step 203, and the fuel consumption and energy storage system degradation index are calculated.

[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 for braking and drive systems> Step 1102 is the process of calculating the input power of the braking and driving device. Based on the control state stored in the time-run curve table, the calculation is performed using equations (12) to (16). Note that if the input power of the braking and driving device calculated in the process of calculating energy consumption in step 604 is stored, it is not necessarily required to recalculate 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 device. Since the power generation device 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. Figure 12(a) shows 1201, which is a power generation command information control table representing 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 time-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 energy storage devices> 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).

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[0079] Figure 13 shows an example of a simulation results table. Figure 13, section 1301, 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 state of charge (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 regular 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 the process of calculating fuel consumption and energy storage device degradation index for a fixed-time run curve.

[0082] <Fuel Consumption Calculation> Fuel consumption is calculated using formula (29).

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[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 Indicator> The degradation index for the energy storage device is calculated using equation (32) for the maximum temperature of the energy storage device, equation (33) for the root mean square of the charge and discharge current, equation (34) for the average state of charge (SOC), and equation (35) for the sum of the absolute values ​​of the charge energy and the absolute values ​​of the discharge energy.

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[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 shows an example of the configuration of the control system for a 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 rest of the configuration is the same as in Example 1, so we will omit the explanation.

[0090] [Overview of the processing of the run curve generation apparatus in Example 2] Figure 15 shows an example of the processing flow of the run curve generation apparatus in Example 2. The processing overview of the run curve generator 1405 will be explained according to 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] Steps 201, 202, and 203 in Figure 15 are the same as those described in Example 1, so 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] The processes in steps 206 and 207 of Figure 15 are the same as those described in Example 1, so their explanation will be omitted.

[0096] [Step 1500 (Adjustment process for the tolerance range of the energy storage device degradation index and the fuel cell degradation index)] The details of the adjustment process for the allowable range of the fuel cell degradation index in step 1500 will be explained. The adjustment for the allowable range of 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 factors 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 acceptable range for fuel cell degradation indicators should be determined after conducting fuel cell cycle tests and considering the expected degradation amount until the fuel cell replacement time. However, in reality, fuel cells may be used in ways different from the design assumptions, or there may be errors in the design assumptions, meaning that the acceptable range determined at the time of design 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 allowable range of the fuel cell degradation index 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. Figure 16 illustrates the adjustment of the allowable range of the fuel cell degradation index according to the degradation state during fuel cell power generation at its rated current.

[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. 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 tolerance 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 acceptable range for fuel cell degradation indicators> Figure 16, item 1602, is a table showing the allowable range of 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 allowable range 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 allowable range 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)] Step 1504 describes the calculation process for fuel consumption, energy storage device degradation index, and fuel cell degradation index.

[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. However, the processes in steps 1101, 1102, 1103, and 1104 are the same as those described in Example 1, so their 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 indicators, is calculated by looking at the power generation from the beginning in the simulation results table shown in Figure 13, item 1301, 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).

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[0108] With the configuration of Embodiment 2 described above, it is possible to generate a run curve that reduces 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 shows an example of the configuration of the control system for a hybrid railway vehicle in Example 3. The configuration of the control system in Example 3 will be explained with reference to Figure 18.

[0111] The control system of 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 driving 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 driver assistance information display device 1807 presents the run curve information 115, input from the run curve generation device 105, to the driver of the hybrid railway vehicle as support information. Both real-time presentation during operation and presentation before the start of operation are possible methods of presentation.

[0114] Figure 19 shows an example of driver assistance information. Figure 19(a), item 1901, is an example of the presentation of real-time driver assistance information while driving. Real-time driving assistance information could include the number of notches for power and deceleration, the next operation, the speed at which the next operation is switched, and the distance to the point where the next operation is switched. The number of notches for power and deceleration can be displayed by referring to the run curve information 115 at the current driving position and obtaining the notch information. For the next operation, the run curve information 115 is searched from the current driving position in the direction of the next station, the point at which the notch or control state at the current driving position switches to a different notch or control state is found, and the notch or control state at that point is obtained and displayed. The speed at which the next operation is switched can be displayed by obtaining the speed at the aforementioned switching point, and the distance to the next operation can also be displayed 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, audio, or other methods to represent it.

[0115] Figure 19(b), item 1902, is an example of the presentation of driver assistance information before starting to drive. Before starting a journey, driver assistance information could be presented as a speed profile, plotting the run curve to the next station with position on the horizontal axis and speed on the vertical axis. Additionally, displaying information such as the number of power notch stages, control status, and switching timing alongside the speed profile would make it easier to understand what operations to perform and at what timing to achieve both reduced fuel consumption and prevention of energy storage system degradation. The rest of the configuration is the same as in Example 1, so we will omit the explanation.

[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 components of the control system for the hybrid railway vehicle in Example 4] Figure 20 shows an example of the main components of the control system for a hybrid railway vehicle in Embodiment 4. The main components of the control system in Example 4 will be explained with reference to 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 with the run curve presentation device 2007. The rest of the configuration is the same as in Example 1, so we will omit the explanation.

[0119] <Conditional Input IF> The condition input IF2001 acquires information about the station intervals 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, via 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 displayed is the same as 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] (Additional 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 those configurations are omitted. Furthermore, it is possible to add or replace some of the configurations of one embodiment with the configurations of another embodiment. Here are some examples of variations:

[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 energy storage device temperature, the root mean square of the charge / discharge current, the average State of Charge (SOC), 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 above), upper limit of power notch (below 50 km / h), upper limit of deceleration notch (50 km / h or above), upper limit of deceleration notch (below 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 available 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. Any method that correlates with the degradation state of the fuel cell can be used.

[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 driver 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 displayed on the driver assistance information display device even while driving. Furthermore, any driver assistance information related to the run curve can be displayed. The same applies to the run curve information presented by the run curve presentation device of 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] The following are possible embodiments of the present invention, but are not limited thereto. (Aspect 1) A run curve generating device for a hybrid railway vehicle that runs using a power generator and an energy storage device as power sources, Create multiple run curve candidates, The method is characterized by determining the run curve on which the hybrid railway vehicle travels, 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, selected from the plurality of run curve candidates. A device for generating the run curve of hybrid railway vehicles.

[0132] (Aspect 2) In the run curve generation device for a hybrid railway vehicle described in Embodiment 1, The degradation index of the energy storage device is calculated for the run curve candidate, The method is characterized in that, among the candidate run curves in which the energy storage device degradation index falls within a first permissible range, the run curve with the lowest fuel consumption is selected as the run curve on which the hybrid railway vehicle will travel. A device for generating the run curve of hybrid railway vehicles.

[0133] (Aspect 3) In the run curve generation device for a hybrid railway vehicle described in Embodiment 2, The first permissible range of the degradation index of the energy storage device is changed according to the temperature or degradation state of the energy storage device. A device for generating the run curve of hybrid railway vehicles.

[0134] (Aspect 4) In the curve generation device for a hybrid railway vehicle according to any one of Aspects 1 to 3, characterized by creating a plurality of curve candidates by changing a combination of conditions of one or more adjustment parameters that affect the curve. Curve generation device for a hybrid railway vehicle.

[0135] (Aspect 5) In the curve generation device for a hybrid railway vehicle according to Aspect 4, the adjustment parameter includes a power notch and a deceleration notch, and different conditions can be set according to the speed of the hybrid railway vehicle respectively, Curve generation device for a hybrid railway vehicle.

[0136] (Aspect 6) In the curve generation device for a hybrid railway vehicle according to any one of Aspects 1 to 5, the energy storage device degradation index includes any one of a maximum energy storage device temperature, a root mean square of the square of the charge-discharge current, an average SOC value, or a sum of an absolute value of charge energy and an absolute value of discharge energy, Curve generation device for a hybrid railway vehicle.

[0137] (Aspect 7) In the curve generation device for a hybrid railway vehicle according to any one of Aspects 2 to 6, in addition to calculating an energy storage device degradation index for the curve candidate, at least one power generation device degradation index that affects the degradation of the power generation device is calculated, among the curve candidates in which the energy storage device degradation index and the power generation device degradation index are respectively within a first allowable range and a second allowable range, the curve with a small fuel consumption is determined as the curve on which the hybrid railway vehicle travels, Curve generation device for a hybrid railway vehicle.

[0138] (Pattern 8) In the run curve generation device for a hybrid railway vehicle described in Embodiment 7, The aforementioned power generation equipment degradation index is characterized by including one of the following: the number of load fluctuations or the average power generation. A device for generating the run curve of hybrid railway vehicles.

[0139] (Aspect 9) In the run curve generation device for a hybrid railway vehicle according to embodiment 7 or 8, The first permissible range of the energy storage device degradation index is changed according to the temperature and degradation state of the energy storage device, The method is characterized by changing the second permissible range of the power generation device degradation index according to the degradation state of the power generation device. A device for generating the run curve of hybrid railway vehicles.

[0140] (Aspect 10) A run curve generating device for a hybrid railway vehicle according to any one of embodiments 1 to 9, The invention is characterized by outputting driver assistance information to support the driver of the hybrid railway vehicle based on the run curve over which the hybrid railway vehicle travels. A device for generating the run curve of hybrid railway vehicles.

[0141] (Aspect 11) A run curve generating device for a hybrid railway vehicle according to any one of embodiments 1 to 10, The temperature and degradation status of the energy storage device, as well as the degradation status of the power generation device, are input via a human-machine interface. A device for generating the run curve of hybrid railway vehicles.

[0142] (Aspect 12) A hybrid railway vehicle equipped with a run curve generation device for a hybrid railway vehicle as described in any one of embodiments 1 to 11.

[0143] (Aspect 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, Create multiple run curve candidates, The method is characterized by determining the run curve on which the hybrid railway vehicle travels, 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, selected from the plurality of run curve candidates. A method for generating a run curve for hybrid railway vehicles. [Explanation of Symbols]

[0144] 101, 1401... Power generation equipment 102... Energy storage device 103... Driving and braking system 1032... Auxiliary equipment 104... Energy Management Device 105, 1405, 2005... Run curve generator 106...Train control system 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...Conditional Input IF 2007... Run Curve Display Device 2011... Input Condition Information

Claims

1. A run curve generating device for a hybrid railway vehicle that runs using a power generator and an energy storage device as power sources, Create multiple run curve candidates, The method is characterized by determining the run curve on which the hybrid railway vehicle travels, 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, selected from the plurality of run curve candidates. A device for generating the run curve of hybrid railway vehicles.

2. In the run curve generation device for a hybrid railway vehicle according to claim 1, The degradation index of the energy storage device is calculated for the run curve candidate, The characteristic is that, among the candidate run curves in which the energy storage device degradation index is within a first allowable range, the run curve with the lowest fuel consumption is determined as the run curve on which the hybrid railway vehicle will travel. A device for generating the run curve of hybrid railway vehicles.

3. In the run curve generation device for a hybrid railway vehicle according to claim 2, The first permissible range of the degradation index of the energy storage device is changed according to the temperature or degradation state of the energy storage device. A device for generating the run curve of hybrid railway vehicles.

4. In the run curve generation device for a hybrid railway vehicle according to claim 1, This method is characterized by creating multiple run curve candidates by changing the combination of conditions for one or more adjustment parameters that affect the run curve. A device for generating the run curve of hybrid railway vehicles.

5. In the run curve generation device for a hybrid railway vehicle according to claim 4, The adjustment parameters include a power notch and a deceleration notch, and are characterized in that different conditions can be set for each depending on the speed of the hybrid railway vehicle. A device for generating the run curve of hybrid railway vehicles.

6. In the run curve generation device for a hybrid railway vehicle according to claim 1, The aforementioned energy storage device degradation index is characterized by including one of the following: the maximum energy storage device temperature, the root mean square of the charge / discharge current, the average SOC value, or the sum of the absolute values ​​of the charge energy and the absolute values ​​of the discharge energy. A device for generating the run curve of hybrid railway vehicles.

7. In the run curve generation device for a hybrid railway vehicle according to claim 2, In addition to calculating the energy storage device degradation index for the aforementioned run curve candidate, at least one power generation device degradation index that affects the degradation of the power generation device is calculated. The method is characterized by selecting a run curve with low fuel consumption from among run curve candidates whose energy storage device degradation index and power generation device degradation index are within a first and second allowable range, respectively, as the run curve on which the hybrid railway vehicle will travel. A device for generating the run curve of hybrid railway vehicles.

8. In the run curve generation device for a hybrid railway vehicle according to claim 7, The aforementioned power generation equipment degradation index is characterized by including one of the following: the number of load fluctuations or the average power generation. A device for generating the run curve of hybrid railway vehicles.

9. In the run curve generation device for a hybrid railway vehicle according to claim 7, The first permissible range of the energy storage device degradation index is changed according to the temperature and degradation state of the energy storage device, The method is characterized by changing the second permissible range of the power generation device degradation index according to the degradation state of the power generation device. A device for generating the run curve of hybrid railway vehicles.

10. A run curve generating device for a hybrid railway vehicle according to claim 1, The invention is characterized by outputting driver assistance information that assists the driver of the hybrid railway vehicle in operating on the run curve of the hybrid railway vehicle. A device for generating the run curve of hybrid railway vehicles.

11. A run curve generating device for a hybrid railway vehicle according to claim 9, The temperature and degradation status of the energy storage device, as well as the degradation status of the power generation device, are input via a human-machine interface. A device for generating the run curve of hybrid railway vehicles.

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, Create multiple run curve candidates, The method is characterized by determining the run curve on which the hybrid railway vehicle travels, 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, selected from the plurality of run curve candidates. A method for generating a run curve for hybrid railway vehicles.

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