Method for operating an electric drive system of a motor vehicle

Abstract

The invention relates to a method for operating an electric drive system of a motor vehicle, comprising at least one fuel cell and at least one battery. The invention is characterised in that an operating strategy is determined in real time using a computing unit disposed in the vehicle, wherein the operating strategy is aimed at achieving a constant power specification with low operating points, so that the fuel cell is operated continuously with constant power.

Description

[0001] Method for operating an electric drive system of a motor vehicle

[0002] The invention relates to a method for operating an electric drive system of a motor vehicle. The electric drive system comprises at least one fuel cell.

[0003] The motor vehicle can, in particular, be a truck with a fuel cell as its primary energy source. The problem with such vehicles or trucks is that the drive power fluctuates greatly depending on the route and prevailing traffic conditions, resulting in an equally fluctuating or uncontrollable energy demand for the drive. This fluctuating energy demand must be provided by the fuel cell and a buffer battery.

[0004] For economic reasons, the buffer battery should not be too large. Therefore, the energy fluctuation is usually attributed to the fuel cell.

[0005] Severely fluctuating power levels and operating points with very high power levels have a detrimental effect on the fuel cell. In particular, the service life of the fuel cell is severely impaired or negatively impacted. Furthermore, fluctuating power levels and high operating points lead to an overall poor efficiency of the fuel cell, resulting in high hydrogen consumption.

[0006] In the past, various methods have therefore been tested to improve the available power or energy requirement of the fuel cell, particularly in conjunction with the buffer battery. DE 102020 004 102 A1 describes a method for operating an electric drive system of a motor vehicle, comprising a buffer battery and a fuel cell for providing electric drive power. Route data and, based on this, consumption data are forecast. Based on the forecast consumption data, a total energy requirement for the route is determined. Based on this, an average fuel cell power is determined, which is required, together with the energy stored in the buffer battery at the start of the route, to determine the total energy requirement for the fuel cell over a constant power trajectory.Consequently, a phlegmatic power trajectory with maximum use of all recuperation potentials as well as a maximum available drive power is calculated.

[0007] For further information on the state of the art, reference can also be made to DE 102020 114269 A1, which also describes a method for operating a fuel cell vehicle. First, expected driving resistances are determined from a future route, and then parameters are recorded that determine the performance of the fuel cell with the buffer battery. A speed can then be determined that is uniform over the future route. The power provided by the fuel cell vehicle is limited to a value required to achieve the speed.

[0008] DE 102017213 088 A1 discloses a method for operating a purely electrically powered motor vehicle with a fuel cell. Predictive consumption data is determined based on navigation data and route information. Based on this, the fuel cell is operated with the greatest possible efficiency.

[0009] Therefore, methods are known from the state of the art that determine the utilization of the fuel cell and the buffer battery based on the maximum available drive power. This involves, among other things, calculating a phlegmatized power trajectory, which is calculated based on maximum utilization of all recuperation potentials and at the maximum available drive power. The disadvantage is that the calculation is based on the total maximum available power, which also negatively impacts the service life of the fuel cell and the buffer battery.

[0010] The object of the present invention is to provide a method for operating an electric drive system of a motor vehicle which overcomes the aforementioned disadvantages.

[0011] According to the invention, this object is achieved by a method having the features in claim 1, and in particular in the characterizing part of claim 1. Advantageous embodiments and further developments emerge from the dependent claims.

[0012] At the core of the method according to the invention, an operating strategy is determined in real time using a computing unit arranged in the vehicle. The operating strategy aims for a constant power specification with low operating points so that the fuel cell operates continuously at a constant power. This aims to achieve a balance between energy efficiency, service life, and power availability via control parameters. Energy efficiency particularly considers recuperation potential. Power availability can take into account driving performance and available drive torque. In particular, an adjustable weighting between energy consumption and the service life of the fuel cell can be used, whereby individual boundary conditions can be taken into account.

[0013] Overall, the service life of the fuel cell and the buffer battery can be improved or optimized. Furthermore, hydrogen consumption can be reduced on routes with challenging topography. In particular, acute energy shortages during peak load phases can be avoided. Overall, the vehicle's operating costs can be reduced and its performance improved.

[0014] In other words, the performance of the fuel cell is phlegmatized, whereby the attempt is not made to operate the fuel cell at its optimum efficiency or to switch it off as much as possible, but rather to operate the fuel cell continuously at a constant power.

[0015] The method is designed for operating an electric drive system of a motor vehicle, wherein the electric drive system comprises at least one fuel cell and at least one battery. In particular, an operating strategy is determined in real time using a computing unit on board the vehicle, using only low computing power and a heuristic approach. The goal is to achieve the most constant power specification possible with the lowest possible operating points.

[0016] Preferably, the constant power can be determined from predetermined route data. This constant power does not refer to a maximum available power, but rather to an optimized power for operating the fuel cell and maintaining a sufficient charge level of the buffer battery.

[0017] According to a very advantageous development of the concept, the power generation by the fuel cell can be adjusted when the battery's state of charge falls below a minimum threshold or exceeds a maximum threshold. This can also extend the service life of the buffer battery and improve its efficiency.

[0018] According to an advantageous embodiment, it can be provided that a route plan is adjusted to operate the fuel cell at a constant power level. Since strongly fluctuating power levels and high-power operating points have a damaging effect on the fuel cell and shorten its service life, the route itself is adjusted, for example, to enable operation at a constant power level.

[0019] A further advantageous embodiment can provide for the operating strategy to be adjusted taking into account mileage, energy efficiency, and the service life of the fuel cell. The adjustment can take place on board the vehicle while driving, allowing for individual adjustments or unforeseen events to be taken into account. According to a very advantageous development of the concept, the vehicle can be a truck used to transport goods. This would, for example, be a transport vehicle subject to fleet management.

[0020] A further advantageous embodiment may provide for data from a transport order and a planned route to be transferred to a data cloud system, where the data is combined with weather data, traffic data, and / or vehicle-specific data and forwarded as a data set to a horizon module. This allows the operating strategy to be adjusted just-in-time when the boundary conditions change.

[0021] According to an advantageous embodiment, the horizon module can be located in the vehicle. This can, for example, provide a rolling horizon based on the current position of the vehicle, which includes data on gradients, curves, traffic flow, and weather along the specified route.

[0022] According to a very advantageous development of the concept, a simulation module can be used to determine the energy requirement for the transport order, taking into account a driving strategy, a speed profile, a drive and braking torque, and / or a drive and braking power. The simulation module then calculates a speed profile for the planned route. The simulation module can, for example, simulate an entire horizon. This takes into account, for example, the maximum possible performance of the drive system, weather conditions, temperature conditions, and any resulting additional limitations on the drive system's performance.

[0023] According to an advantageous embodiment, it can be provided that the simulation module forwards the calculated data to a segmentation module, wherein the segmentation module categorizes the data determined by the simulation module and then compares it with underlying limit values ​​to optimize the service life of the fuel cell, wherein the calculated data is optimized for at least parts of the planned route if a minimum limit value is undershot and / or a maximum limit value is exceeded. The parts of the planned route can be determined, for example, by a horizon segmentation module, wherein the horizon can be divided into use cases depending on the locally required drive or braking power. For example, a low load, a partial load, a full load and recuperation can be used as a basis.

[0024] Further advantageous embodiments of the method according to the invention also emerge from the exemplary embodiment which is described in more detail below with reference to the figures.

[0025] Showing:

[0026] Fig. 1 is a flowchart of an embodiment of the method;

[0027] Fig. 2 shows a further flow diagram of an embodiment of the method; and Fig. 3 shows a further flow diagram of an embodiment of the method.

[0028] Fig. 1 shows a possible flow diagram of the method. It describes a predictive power control of a fuel cell as an example. In step 1, a driver, a fleet manager or a dispatcher can plan a transport order including a tour. Information about the planned route, the corresponding vehicle and, if applicable, information about the driver can be provided. In step 2, this transport order can be transmitted to a data cloud system, where it can be enriched with additional data such as weather, traffic and / or vehicle-specific data and forwarded as a tour data set to a horizon module 3. The horizon module 3 is preferably located on board the vehicle and can, for example, determine a rolling horizon based on a current position of the vehicle.The rolling horizon can contain data from gradient, curvature, traffic flow, and the prevailing weather along the specified route plan. The rolling horizon can be made available to a simulation module 4. In particular, the horizon has a specified route length, which must be longer in challenging topography with large elevation differences than in flatland. Longer means, in particular, in a range of 50–100 km, although in flatland, a route of less than 50 km may prevail. Simulation module 4 can simulate the entire horizon, taking the driving strategy into account, and generate an assumed realistic speed profile with the associated drive and braking torque or drive and braking power. This can be used to derive an energy requirement.In particular, the maximum possible performance of the drive system can be considered, taking into account weather and temperature conditions and the resulting additional limitations on the drive system's performance. Traffic-related disruptions that affect a reduced driving speed can also be taken into account. The simulation module 4 can forward the created simulation with the relevant data to a horizon segmentation module 5. The relevant data can include drive and braking torques, required power and energy input, recuperable power and energy, average energy demand, speed profile, temperature forecasts, or cooling circuits.

[0029] The horizon segmentation module 5 can divide the horizon into use cases depending on the locally required drive or braking power. For example, a low load may exist, which defines a drive power less than the maximum fuel cell power. In the case of partial load, a drive power higher than the maximum fuel cell power but lower than the maximum drive motor power may exist. In the case of full load, the required drive power may be higher than the available maximum engine power when driving uphill, which slows the vehicle down. In the case of recuperation, a braking torque or negative drive torque from driving downhill can be used to recover energy in the battery or store it there.

[0030] All data from the simulation or horizon segmentation can be transferred to a further module 6. The previously determined data can be calculated in a simulation module 8 over an entire horizon with a fuel cell power assumed to be constant, which corresponds to the previously calculated average energy demand from step 4 less the determined recuperation energy. A check can then be performed to determine whether the specified SOC limit values ​​have been exceeded or undershot. If no violations occur, the determined fuel cell power can be provided for a predefined period of time in steps 10 and 11, until a new horizon is provided and a new calculation can begin with step 3.

[0031] If an SOC violation is detected at an upper SOC limit, the horizon can be divided into two sub-horizons. The division can occur at a use boundary between an affected use case and a subsequent use case from the classification. A new simulation calculation can then be performed with both parts of the horizon in simulation module 8. The first part of the horizon, with the SOC violation at the end, can be re-simulated in such a way that the upper SOC limit is no longer violated. This can be achieved, for example, by reducing the fuel cell output or by reducing the recuperation phases. This depends on a target that determines whether the focus is on energy efficiency (reduced fuel cell output) or fuel cell aging (reduced recuperation potential). This is shown, for example, in Figure 3.Such a differentiation or weighting can be controlled using appropriate parameters, such as a lifetime parameter. The extent of the reduction can be derived from the amount of energy that lies above the SOC limit. The second partial horizon can then be simulated using the new, corrected starting value. The second partial horizon can also be checked for further SOC violations. If no violation is detected, the partial horizon can be passed on to steps 11 and 12, just like the first, previous partial horizon. If an SOC violation is detected again, the entire process from step 6 to step 10 must be repeated. This can result in recurring, uniform processes, so recursive programming is advantageous for these steps.

[0032] If a lower SOC limit violation is detected, the horizon can also be divided into two sub-horizons. In the first horizon section, the fuel cell power can be increased such that the lower SOC limit violation can no longer occur. If a sufficient increase in fuel cell power is no longer possible because the maximum possible available fuel cell power has been exhausted, or if limiting the cooling system is not desired, a reduction in driving performance can be implemented in the affected horizon section. Furthermore, analogous to the limit violation at the upper SOC limit, a reduced or completely suppressed increase in fuel cell power can be implemented here, controlled via a lifetime parameter, which then also leads to reduced driving performance.If reduced driving performance occurs, the drive power must be simulated again and the use cases reclassified with reduced drive power, in order to subsequently perform a further check for SOC violations. This is shown, for example, in Figure 2. For example, if limitations of the thermal management system are detected, it is possible to set a lower upper limit for the fuel cell power in order to transition to reduced driving performance in a timely manner. The second sub-horizon can be simulated again with a higher SOC starting value and checked for any remaining violations. In the event of an SOC violation, steps 6 to 10 can be repeated.

[0033] An associated algorithm for the method steps described above can be seen in Fig. 2 and 3. The algorithm shown in Fig. 2 describes a downward SOC violation, where there is too little energy in the horizon. In step 21, it can be determined whether an SOC violation has occurred. A decision is then made in step 24 as to whether or not power mode should be started. If power mode is started, the fuel cell power is increased in step 23 until the energy deficit is compensated. If power mode is not to be started, the fuel cell power can be increased proportionally in step 25. Service life parameters can be taken into account in step 26. Likewise, power limitations of a thermal management system and a battery management system can be taken into account in step 22.

[0034] The same can be considered in step 20 when increasing the fuel cell power. After step 23, step 27 checks whether the energy demand is met. If this is the case, the corresponding process is implemented in step 31. If this is not the case, the driving performance is initially reduced by a corresponding shortfall in step 29. If power mode is not activated, a decision is made in step 28 as to whether the driving performance is acceptable or not. If this is the case, the corresponding process is implemented in step 31. If this is not the case, the fuel cell power is initially increased until the minimum required driving performance is reached (step 30).

[0035] Fig. 3 shows a further flow diagram of an embodiment of the method, wherein an SOC violation is shown upwards, with too much energy present in the horizon. Accordingly, an energy surplus is detected in step 21. In step 24, it is therefore determined whether an energy mode should be started. Accordingly, in step 23, a reduction in the fuel cell power can be compensated for up to an energy surplus. In step 25, a proportional reduction in the fuel cell power can take place. In step 27, it is checked whether energy compensation was possible; if this was not the case, a reduction in recuperation can take place in step 29. Accordingly, in step 28, it can be checked whether braking power was sufficient so that an energy surplus is compensated for. If this is not the case, the fuel cell power can be reduced in step 30 down to a minimum required braking power.

Claims

Patent claims 1. A method for operating an electric drive system of a motor vehicle, comprising at least one fuel cell and at least one battery, characterized in that an operating strategy is determined in real time using a computing unit arranged in the vehicle, wherein the operating strategy aims at a constant power specification with low operating points, so that the fuel cell is operated continuously with constant power.

2. Method (1) according to claim 1, characterized in that the constant power is determined from predetermined route data.

3. Method (1) according to claim 1 or 2, characterized in that a power generation by the fuel cell is adjusted when a state of charge of the battery falls below a minimum limit value or exceeds a maximum limit value.

4. Method (1) according to claim 1, 2 or 3, characterized in that a route planning is adapted in order to operate the fuel cell with constant power.

5. Method (1) according to one of claims 1 to 4, characterized in that an adaptation of the operating strategy takes place taking into account a driving performance, an energy efficiency and a service life of the fuel cell.

6. Method (1) according to one of claims 1 to 5, characterized in that the vehicle is a truck used for transporting goods.

7. Method (1) according to claim 6, characterized in that Data from a transport order and a planned route are transferred to a data cloud system, where the data is combined with weather data, traffic data and / or vehicle-specific data and forwarded to a horizon module as a data set.

8. Method (1) according to claim 7, characterized in that the horizon module is located in the vehicle.

9. Method (1) according to one of claims 7 or 8, characterized in that an energy requirement for the transport order is determined by a simulation module, wherein a driving strategy, a speed profile, a drive and braking torque and / or a drive and braking power are taken into account, and wherein the simulation module calculates a speed profile for the planned route.

10. Method (1) according to claim 9, characterized in that the simulation module forwards the calculated data to a segmentation module, wherein the segmentation module categorizes the data determined by the simulation module, and then compares them with underlying limit values ​​for lifetime optimization of the Fuel cell, whereby an optimization of the calculated data of at least parts of the planned route takes place if a minimum limit is not reached and / or a maximum limit is exceeded.

11. Method (1) according to one of the preceding claims, characterized in that with the aid of a control parameter, in the event of an excess of available energy in the forecast horizon, a balance can be made between recuperation to increase energy efficiency or a reduced reduction in fuel cell power to improve the service life of the fuel cell.

12. Method (1) according to one of the preceding claims, characterized in that with the aid of a control parameter, in the case of an undersupply of available energy in the forecast horizon, a balance can be struck between an increase in the fuel cell performance at the expense of the service life of the fuel cell or a reduced driving performance.

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