Route planning for improving braking performance of fuel cell powered vehicles

Abstract

The application relates to routing for improving braking performance of a fuel cell powered vehicle, in particular to a computer system (130, 140) for a heavy vehicle (100) comprising a fuel cell system (111) and an electrical energy storage system (ESS) (112, 121), where the computer system (130, 140) comprises processing circuitry configured to process the fuel cell system (111) and the ESS (112, 121). The processing circuitry is configured to: identify (S1) a downhill portion (C) of a trip to be made by the heavy vehicle (100), determine (S2) at least two candidate routes (R1, R2) from a starting position (A) along the trip to a starting point (B) of the downhill portion (C) of the trip, predict (S3) for each candidate route (R1, R2) an energy state SoE of the battery system at the starting point (B) of the downhill portion (C), and determine (S3) a state of energy SoE of the battery system at the starting point (B) of the downhill portion (C). And selecting (S4) a suggested route from the candidate routes (R1, R2) based at least in part on the predicted SoE of each candidate route and on an estimated amount of energy regenerated by traversing the downhill portion (C) of the trip.

Description

Technical Field

[0001] The present disclosure generally relates to route planning for electric road vehicles. In particular aspects, the present disclosure relates to route planning for improving the retarding braking performance of fuel cell powered vehicles. The present disclosure may be applicable to heavy vehicles such as trucks, buses and construction equipment, as well as other vehicle types. Although the present disclosure may be described with respect to a particular vehicle, the present disclosure is not limited to any particular vehicle. Background Art

[0002] Electric vehicles are becoming increasingly common. The electric motors on electric vehicles can be used for both propulsion and braking, which is an advantage because at least some of the electrical energy expended in accelerating the vehicle can be recovered during braking, thereby improving overall energy efficiency.

[0003] Fuel cell systems for cars have been known for some time. Fuel cells have the advantage of using hydrogen to generate electricity in an environmentally friendly manner. Battery-powered vehicles can use on-board fuel cell systems to convert hydrogen into electricity, thereby significantly extending the range of the electric vehicle.

[0004] Despite the progress made to date in the development of battery electric and fuel cell powered electric vehicles, there remains a need for improved methods of operating such vehicles. Summary of the invention

[0005] According to a first aspect of the present disclosure, a computer system for a heavy vehicle is provided, wherein the vehicle includes a fuel cell system, an electrical energy storage system (ESS) (such as a battery system or a supercapacitor device) and a processing circuit. The processing circuit is configured to identify a potentially problematic downhill portion of a trip to be performed by the heavy vehicle, and determine at least two candidate routes leading from a starting position along the trip to the starting point of the potentially problematic downhill portion. The processing circuit is also configured to predict the state of energy (SoE) of the ESS at the starting point of the downhill portion for each candidate route, and select a recommended route from the candidate routes based at least in part on the predicted SoE of each candidate route and an estimated amount of energy regenerated by traversing the downhill portion of the trip. This first aspect of the present disclosure can seek to improve the braking performance, particularly slow braking performance, of a fuel cell powered vehicle, thereby allowing the vehicle to traverse long downhill sections more safely and efficiently. The system automatically generates a route selection suggestion, which helps an operator of the vehicle (such as a driver or an autonomous driving algorithm) to operate the vehicle safely and efficiently.

[0006] According to some aspects, the heavy-duty vehicle includes a fuel cell system arranged to pre-charge the ESS prior to an uphill portion of a journey that the heavy-duty vehicle is to traverse. An advantage is that the computer system can be configured to account for such pre-charging operations, as they may result in saturation of the ESS if not properly accounted for.

[0007] According to some other aspects, the processing circuit is configured to predict the SoE of the ESS at least in part by considering the predicted fuel cell charging operation along each candidate route. The prediction can be obtained in a number of different ways as will be described below. By considering the expected fuel cell charging operation along each candidate route, a better prediction of the SoE at the beginning of the downhill portion is obtained. This feature improves the prediction of the SoE of the ESS at the beginning of the downhill portion for each candidate route because the different expected operation of the fuel cell system along each candidate route is more accurately considered.

[0008] The processing circuitry may also be configured to predict, for each candidate route, the SoE of the ESS at the beginning of the downhill portion by at least in part identifying uphill portions along the candidate route. Such uphill portions may be readily identified, for example from digital map data or records made by vehicles previously traveling on the candidate route, and typically have a significant impact on the SoE of the ESS. Thus, the prediction of the SoE at the beginning of the downhill portion is improved.

[0009] According to other aspects, the processing circuit is configured to implement a digital twin of the energy system of the heavy vehicle, i.e., a digital model of the operating principles of the different vehicle energy system components, and predict the SoE of the ESS at the beginning of the downhill portion for each candidate route based at least in part on the digital twin. The digital twin, which is a model of the vehicle and its energy consumption and generation operations, can be used to obtain accurate information about how the SoE is likely to evolve when the vehicle follows a given route with a given terrain curve. Using the digital twin in this way improves the prediction of the SoE at the beginning of the downhill portion.

[0010] The processing circuitry may also be configured to receive pre-recorded SoE curve data for at least a portion of a trip to be made by the vehicle from an onboard data storage device and / or from a remote server, in which case the processing circuitry may be configured to predict the SoE of the ESS at the start of the downhill portion for each candidate route based at least in part on the pre-recorded SoE curve data. This may result in a more reliable prediction, which is an advantage.

[0011] According to some aspects, the processing circuit is configured to select a suggested route from two or more candidate routes based at least in part on an energy storage capacity of the ESS. Some vehicles may be able to store more energy than other vehicles and therefore may be able to perform slow braking for a longer period of time. By considering the energy storage capacity of the ESS in this manner, a more optimal route may be selected, for example, a route that is shorter and / or faster but includes more hilly portions. The processing circuit may also be configured to determine a current energy storage capacity of the ESS based at least in part on an ambient temperature of the vehicle, which generally affects the energy storage capacity of the ESS and the ability to dissipate energy by cooling heated components (such as friction brakes, brake resistors, etc.).

[0012] The heavy vehicle optionally includes an energy dissipation device, such as a brake resistor arrangement. In this case, the processing circuit can be configured to select the suggested route from the candidate routes based at least in part on the energy dissipation capacity of the energy dissipation device. The processing circuit can, for example, be configured to determine the current energy dissipation capacity of the energy dissipation device based at least in part on the current temperature of the energy dissipation device.

[0013] According to some aspects, the processing circuit may also be configured to select a suggested route from the candidate routes based at least in part on the retarding braking capability and / or cooling capability of the service brake system of the heavy vehicle. The service brake system, although not capable of retarding braking for a long period of time, may still be used to provide a certain braking effect. By considering the capability of the service brake system, a better selection of the candidate routes may be obtained.

[0014] The processing circuit is preferably further configured to recommend stopping ESS discharge along the route preceding the downhill portion when none of the candidate routes meet the SoE acceptance criteria at the start of the downhill portion. This improves overall vehicle operating safety.

[0015] According to some aspects, the processing circuit is configured to record a SoE curve along the trip based on the position of the heavy vehicle. This information can then be used to improve future estimates and predictions for the same vehicle and for other vehicles traveling along the same route. The processing circuit can also be configured to transmit the recorded SoE curve along the trip to an onboard data storage device and / or a remote server.

[0016] It will be appreciated by those skilled in the art that the disclosed aspects, examples (including any preferred examples) and / or the appended claims may be appropriately combined with each other. Additional features and advantages are disclosed in the following description, claims and drawings, and will in part be apparent to those skilled in the art or recognized by practicing the disclosure as described herein.

[0017] Also disclosed herein are computer systems, control units, code modules, computer-implemented methods, computer-readable media, and computer program products associated with the technical benefits discussed above. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Examples are described in more detail below with reference to the accompanying drawings.

[0019] Figure 1 is an exemplary heavy vehicle according to an example.

[0020] Figure 2 Candidate routes leading to a downhill section are shown.

[0021] Figure 3 Selection of the first candidate route is shown.

[0022] Figure 4 Selection of the second candidate route is shown.

[0023] Figure 5 is a flow chart illustrating the method.

[0024] Figure 6 An example computer system is schematically shown. DETAILED DESCRIPTION

[0025] The detailed description set forth below provides information and examples of the disclosed technology in sufficient detail to enable those skilled in the art to practice the disclosure.

[0026] Figure 1 An example heavy vehicle 100 is shown, here in the form of a truck including a tractor 110 and a trailer 120. However, the technology disclosed herein is also generally applicable to other types of vehicles, such as rigid trucks and some passenger cars. The vehicle 100 includes a computer system 130, 140, which may be arranged in the truck and / or trailer. The computer system or parts thereof may also be arranged on a server 170 or the like remote from the vehicle 100, which server may access a radio base station 160 or other type of access point from the vehicle 100 via a wireless link 150. The computer system 130, 140 may include a central processing unit, commonly referred to as an electronic control unit (ECU), or it may be distributed over several separate processing devices. This will be described below in conjunction with the computer system 130, 140. Figure 6 An example computer system is discussed in further detail.

[0027] In some cases, a heavy vehicle may be defined as a freight vehicle weighing more than 3.5 metric tons or a passenger vehicle with more than 8 seats. A heavy vehicle may also be defined as a vehicle with a frontal area greater than 45 square feet (about 4.18 square meters). The teachings herein are particularly suitable for use with semi-trailer type vehicles such as Figure 1The vehicle shown in the figure is used together with a rigid truck (including a rigid truck with a cart and one or more trailers).

[0028] The vehicle 100 includes a fuel cell system 111 that is arranged to generate electricity from hydrogen in a known manner. The electricity can be used to directly power various actuators of the vehicle (such as an electric motor, a power steering system, an electromechanical service brake system, etc.). Some or all of the electricity generated by the fuel cell system 111 can also be stored in an onboard energy storage system (ESS) 112 on the tractor 110 and / or in an ESS 121 arranged on the trailer 120. The most common type of ESS on road vehicles today is a battery system. However, other forms of ESS, such as supercapacitor-based energy storage systems, can of course also be used. Although the following text will mainly relate to battery systems, it should be understood that other forms of ESS can also be used.

[0029] The electric motor on a battery-powered vehicle can typically be used for both propulsion and braking, and can be arranged on both the tractor and the trailer. Energy is consumed during propulsion and is at least partially regenerated during braking when traveling downhill. When an electric vehicle is traveling downhill, it is important that the battery's state of energy (SoE) (usually measured in joules) is not too high at the beginning of the downhill portion of the road. If it is too high, the battery may be fully charged before the end of the downhill portion of the road, which means that the battery can no longer absorb energy from the motor. If there is no other way to dissipate the energy from the motor, the motor can no longer be used for braking. Braking operations over long periods of time and / or downhill distances are generally referred to as creep braking.

[0030] Service brakes (i.e., friction brakes arranged on tractors and trailers) can be used to brake the vehicle in situations where the SoE of the vehicle ESS is too high to allow motor braking. However, service brake systems including friction brakes such as disc brakes or drum brakes are at risk of failure if used for long periods of time, a condition sometimes referred to as brake fade.

[0031] Some vehicles include energy dissipation devices 112, 122, such as brake resistors, which can be used to dissipate excess energy. However, the energy dissipation capacity of such energy dissipation devices is limited. For example, the energy dissipation capacity of a brake resistor is limited by its temperature, which rises during energy dissipation. Some brake resistors include active cooling systems. The cooling capacity of such a cooling system will then also have an impact on the energy dissipation capacity of the brake resistor.

[0032] Figure 2A scenario 200 is shown in which a fuel cell powered heavy-duty vehicle is about to make a trip that passes through a downhill portion C of a road from a location B at the start of the downhill portion C to a location D at the end of the downhill portion C. The trip begins at or passes through location A, where the vehicle 100 selects between a first candidate route R1 and a second candidate route R2, both of which lead from the start location A to the start location B of the downhill portion C. The computer system 130, 140 on the vehicle 100 can determine a maximum allowable SoE 210 at the start location B of the downhill portion C of the trip based on the energy storage capacity of the battery system 112, 121 on the vehicle that allows the vehicle 100 to safely traverse the downhill portion. If the SoE at the start location of the downhill portion C is higher than the maximum allowable SoE 210, as shown in FIG. Figure 2 As shown in the graph in , the battery system may not be able to absorb the energy regenerated during braking, causing the ESS to saturate before reaching the end of the downhill portion C 220. This in turn means that the service brakes will need to be applied near the end of the downhill portion, which may cause service brake failure (e.g., due to brake fade) and increase the risk of an accident because the service brakes are generally not suitable for long periods of slow braking.

[0033] The maximum allowed SoE can be determined in several different ways, with varying degrees of complexity. For example, a predetermined mapping between the height in meters of the downhill portion and the total distance and the maximum allowed SoE can be used to determine how much energy needs to be dissipated. More advanced options include functions that are parameterized by one or more vehicle-related attributes, such as vehicle weight, vehicle type, expected duration of traversing the downhill portion of the road, the ambient temperature of the vehicle, the allowed speed for traversing the downhill portion of the road, etc. The mapping between the downhill portion characteristics and the maximum allowed SoE can be determined in a straightforward manner, either analytically, using models, and / or by actual experimentation. Several methods for calculating the maximum allowed SoE for safely traversing a downhill portion of a road are also known in the prior art, and therefore this topic will not be discussed in detail herein.

[0034] The present disclosure relates to a method and corresponding vehicle computer system for improving braking performance along a trip that includes a long downhill portion where slow braking is required or even necessary. According to the techniques disclosed herein, a potentially problematic downhill portion C of a trip to be performed by a heavy vehicle 100 is first identified based on one or more identification criteria, such as the total length of the downhill portion, the total number of meters of elevation to be traversed, the average gradient of the downhill portion, and the estimated potential energy to be dissipated when traversing the downhill portion C. It should be understood that the identification of potentially problematic downhill portions may be vehicle-specific, as some vehicles may be able to sustain braking for extended periods of time better than other vehicles.

[0035] Then, for example, using known map-based route selection techniques, at least two candidate routes R1, R2 are identified leading from the starting position to the starting point B of the downhill portion C of the trip. The candidate route with the least number of hills is then selected and presented to the driver, where the hills are defined as a portion of uphill driving followed by a portion of downhill driving. The definition of hills can also include a total height requirement from the foot of the hill to the top of the hill, the total height in meters, etc. Some additional constraints (such as the maximum time difference between the fastest route and the selected route, the maximum length difference between the shortest route and the selected route, and the maximum energy consumption difference between the most energy-efficient route and the selected route) can be applied to the selection of candidate routes. Adding such selection constraints reduces the number of candidate routes available for selection, which is an advantage. The proposed route selection technique will now be discussed, illustrated and summarized in more detail.

[0036] Figure 3 Scenario 300 is shown in which the vehicle 100 selects a candidate route R1 from location A to a starting point B of a downhill portion C. The candidate route R1 includes hills, such as Figure 3 As shown in the topology diagram 310 in FIG, the vehicle 100 has to traverse the hill before reaching the downhill portion C. In this case, the fuel cell system 111 precharges the battery systems 112, 121 so as to be able to reach the top of the hill. Therefore, the battery SoE increases before the start of the hill, then decreases as the vehicle drives uphill, and then increases again during the downhill driving until the start of the downhill portion C. The result of driving along the candidate route R1 from the starting position A to the start of the downhill portion C is that the SoE of the battery system is quite high, which is partly due to the fuel cell system using the margin to reach the top of the hill along the candidate route R1 and partly due to regenerating energy during braking along the candidate route R1. Due to the existence of this SoE at the start of the downhill portion C, the vehicle cannot safely traverse the downhill portion. It is an object of the technology disclosed herein to avoid this situation.

[0037] Figure 4 Scenario 400 is shown in which the vehicle 100 instead selects candidate route R2 from the starting location A to the starting point B of the downhill portion C. Figure 4 As shown in the road topography 410 in FIG. 4 , the candidate route R2 instead goes around the mountain, i.e., is flatter than the candidate route R1. In this case, the fuel cell system does not need to charge the battery in advance, there is no downhill section of the road just before the long downhill section C, and therefore the battery system SoE allows slow braking during the downhill section C of the trip, for example.

[0038] The present invention solves or at least alleviates some of the problems associated with slow braking during extended periods of downhill driving of fuel cell powered vehicles. This is accomplished by evaluating a plurality of candidate routes leading to the start of the downhill portion of the journey that the vehicle is to travel. The vehicle's computer system will automatically evaluate each of the candidate routes and suggest the route or routes that will enable the vehicle to safely brake during the downhill portion of the journey. By following the recommendations of the predictive computer system, the vehicle operator can avoid situations where the SoE of the battery is too high to allow adequate slow braking performance during extended periods of downhill driving.

[0039] More simply stated, according to an example, the system evaluates two or more candidate routes leading to a downhill portion of a trip to be traveled by the vehicle, and selects a route from the set of identified candidate routes that does not include a hill to be traveled over to reach the downhill portion, because traveling over such a hill just before traveling along the downhill portion of the trip may result in the SoE at the beginning of the downhill portion being too high.

[0040] In short, also refer to Figure 5 The flowchart and Figure 6 , a computer system 130, 140 for a heavy vehicle 100 is disclosed herein, the heavy vehicle including a fuel cell system 111 arranged to provide power to charge an ESS 112, 121 of the vehicle 100. The ESS may be arranged on a tractor 110 and / or a trailer 120 of a vehicle combination, such as Figure 1 Although ESS typically includes a battery system, other options exist.

[0041] The heavy vehicle 100 typically includes a fuel cell system 111 that is arranged to pre-charge the battery system 112, 121 in advance of an uphill portion of a journey that the heavy vehicle 100 is to traverse. The computer system 130, 140 then monitors the topology of the road ahead along the planned journey using, for example, a map with terrain information, and pre-identifies a need for additional power, such as additional power above the continuous power level that the fuel cell system may need to generate in order to traverse the upcoming uphill section of the road. The pre-provided charge provided by the fuel cell system typically includes an additional amount of margin energy to ensure that the vehicle reaches the top of the hill before the energy in the battery system is exhausted. Therefore, due to the energy margin, the SoE at the top of the hill is typically not close to exhaustion.

[0042] Topography is generally a field of earth science and is usually concerned with local details, including elevation contours or roads, populated areas, structures, land boundaries, etc. Topography in a narrower sense is concerned with the recording of landforms or relief, the three-dimensional qualities of the surface, and the identification of specific landforms; this is also known as geometries. In modern usage, this involves the generation of elevation data in digital form. It is generally considered to include the graphical representation of terrain on a map through various cartographic relief techniques, including contour lines, layered tinting, and relief shading.

[0043] The computer system includes a processing circuit configured to identify the downhill portion C of the trip that the S1 heavy vehicle 100 is about to take. The downhill portion along the trip can be identified by using, for example, a digital map repository including terrain information (i.e., height curve data indicating the change in road height in a certain area). The digital map can be stored on the vehicle 100 or accessed from a remote server as needed. A vehicle traveling from one point to another can use a known path planner to determine candidate routes, and then the terrain along those routes can be analyzed to determine the downhill portion. Various criteria can be used to identify the downhill portion, such as the total descent height (in meters), the total descent rate (in degrees), or the average descent height per unit distance (unitless). A certain minimum length requirement can also be imposed so that the computer system only considers downhill portions with at least a given length. The composition of the downhill portion may vary from vehicle to vehicle, as will be discussed in more detail below. For a vehicle with a relatively small capacity battery system, a given downhill section may be considered problematic, while for another vehicle with a larger capacity battery system, it is considered to be non-problematic. Vehicle weight, service brake system capability, and ambient temperature are other factors that may be considered when identifying downhill portions of a road along a given route.

[0044] The processing circuit is configured to determine S2 at least two candidate routes R1, R2 leading from the starting position A along the trip to the starting point B of the downhill portion C of the trip, as described above with respect to Figures 2 to 4 As discussed in the examples in . Candidate routes can be determined using known path finding algorithms (such as Dijkstra's algorithm implemented on a road grid). Most of today's car navigation systems are able to generate alternative routes from a starting location to a destination. Therefore, route planning methods will not be discussed in more detail in this article.

[0045] The processing circuitry then predicts S3 the SoE of the battery system at the starting point B of the downhill portion C for each candidate route R1, R2, and selects S4 a suggested route from the candidate routes R1, R2 based at least in part on the predicted SoE for each candidate route and an estimated amount of energy regenerated by traversing the downhill portion C of the trip.

[0046] Sometimes, none of the candidate routes will produce an SoE at the start of the downhill portion that allows the vehicle to safely traverse the downhill portion. The processing circuit can therefore be configured to suggest S5 to stop discharging the battery system along the route before the downhill portion C when no candidate route meets the SoE acceptance criteria at the start point B of the downhill portion C.

[0047] Sometimes, generating a candidate route that allows SoE at the start of the downhill portion is too costly in terms of, for example, increased fuel consumption or increased time, etc. In this case, the processing circuit may also suggest S5 to stop discharging the battery system along the route before the downhill portion C.

[0048] The computer system's prediction of SoE may be accomplished at least in part by considering S31 predicted fuel cell charging operations along each candidate route R1, R2. For example, due to an upcoming mountainous road, the computer system may determine that a battery system charge will be performed at a particular point along the trip.

[0049] The estimated amount of energy regenerated by traversing the downhill portion C of the trip may be determined using, for example, a vehicle energy generation capability model (which varies according to the height of the downhill portion C), the approximate weight of the vehicle, and the efficiency of the motor used for regenerative braking. The vehicle energy generation capability model may be determined by actual experimentation and / or by computer simulation using known methods.

[0050] The processing circuitry may also be configured to predict S32 the SoE of the battery system 112, 121 at the starting point B of the downhill portion C for each candidate route R1, R2 by only identifying uphill portions along the candidate routes R1, R2. In other words, the techniques disclosed herein may be implemented in a fairly basic manner by identifying one or more downhill portions that are considered to be potentially problematic, and then suggesting a candidate route among the candidate routes that includes the fewest road uphill portions leading to the one or more downhill portions.

[0051] The computer system may also be configured to take into account other parameters that have an impact on energy consumption along the candidate route, such as road surface conditions, i.e. rolling resistance, air resistance, whether the road surface is wet, etc. This data may be obtained from an onboard data source or from a remote server 170 via wireless link 150 .

[0052] According to a more advanced implementation example, the processing circuit implements a digital twin of the energy system of the heavy vehicle and predicts S33 the SoE of the battery system at the starting point B of the downhill portion C for each candidate route R1, R2 based at least in part on the digital twin. A digital twin is a model of a vehicle that models energy consumption and generation based on, for example, the road topology along the route that the vehicle will traverse. The digital twin may include a full-scale model of the control system on the vehicle, or a simplified model of the control system on the vehicle. By inputting candidate routes and other vehicle parameters corresponding to the physical vehicle, the digital twin can be used to evaluate the evolution of SoE along various candidate routes. The digital twin can also be built to take into account road conditions, such as rolling resistance, and weather conditions, such as wind, rain, snow, etc.

[0053] According to yet another implementation example, the processing circuit is configured to receive S34 pre-recorded SoE curve data for at least a portion of the trip from an onboard data storage device and / or from a remote server 170. The pre-recorded SoE curve data may, for example, have been previously recorded by the same vehicle or by another equivalent vehicle making the same trip. The processing circuit may then be configured to predict S341 the SoE of the battery system at the starting point B of the downhill portion C for each candidate route R1, R2 based at least in part on the pre-recorded SoE curve data. With regard to these features, the processing circuit may also be configured to record the SoE curve along the trip according to the position of the heavy vehicle 100, and also transmit 150 the recorded SoE curve along the trip to the onboard data storage device and / or the remote server 170.

[0054] The suggested route may be automatically selected from different candidate routes in a number of different ways. The processing circuit may, for example, be configured to select S41 the suggested route from the candidate routes R1, R2 based at least in part on the energy storage capacity of the battery systems 112, 121. The greater the energy storage capacity, the more regenerative braking that can be tolerated. Therefore, it should be understood that two different vehicles may have different capabilities in terms of downhill braking capability. A given portion of a trip that is considered a downhill section by one vehicle may not actually be identified as a downhill section by another vehicle equipped with a larger capacity battery system.

[0055] The processing circuit is optionally configured to determine S411 the current energy storage capacity of the battery system 112, 121 based at least in part on the ambient temperature. The energy storage capacity of some battery systems may vary significantly with ambient temperature. Therefore, the slow braking capability of some vehicles may vary significantly with ambient temperature.

[0056] As discussed above, the heavy vehicle 100 may also include an energy dissipation device 113, such as a brake resistor. The processing circuit may then be configured to select S42 a suggested route from the candidate routes R1, R2 based at least in part on the energy dissipation capacity of the energy dissipation device 113. Thus, a vehicle equipped with a large, high-capacity energy dissipation device may be able to traverse a longer downhill portion than a vehicle lacking an energy dissipation system. The processing circuit is optionally also configured to determine S421 the current energy dissipation capacity of the energy dissipation device 113 based at least in part on the current temperature of the energy dissipation device 113, which is an advantage because the energy dissipation capacity of such devices is typically a function of their temperature. For example, a hot brake resistor is closer to its energy dissipation limit than a cold brake resistor.

[0057] The processing circuit may also be configured to select S43 a suggested route from the candidate routes R1, R2 based at least in part on the retarding braking capability and / or cooling capability of the service brake system of the heavy vehicle 100. Different service brake systems have different capabilities in terms of retarding braking. Some service brake systems include advanced water-based cooling systems that allow a large amount of retarding braking to be achieved, while other service brake systems can only handle a limited amount of continuous braking. Fuel cell vehicles generate large amounts of water during energy generation, which can be stored in a storage tank and used to cool the brakes during retarding braking operations. The computer system preferably takes such capabilities into account when selecting a suggested route to be followed before the start of the downhill portion.

[0058] Figure 5 is a flow chart of a method according to an example, which illustrates various operations that may be performed by a computer system 130, 140. A computer-implemented method performed by a computer system 130, 140 in a heavy vehicle 100 including a fuel cell system 111 and battery systems 112, 121 is illustrated. The method includes: identifying S1, by a processing circuit of the computer system, a downhill portion C of a trip to be performed by the heavy vehicle 100; determining S2, by the processing circuit, at least two candidate routes R1, R2 leading from a starting position A along the trip to a starting point B of the downhill portion C of the trip; predicting S3, by the processing circuit, for each candidate route R1, R2, the SoE of the battery system at the starting point B of the downhill portion C; and selecting S4, by the processing circuit, a suggested route from the candidate routes R1, R2 based at least in part on the predicted SoE of each candidate route and based on an estimated amount of energy regenerated by traversing the downhill portion C of the trip.

[0059] Figure 66 is a schematic diagram of a computer system 600 for implementing the examples disclosed herein. The computer system 600 is suitable for executing instructions from a computer-readable medium to perform these and / or any functions or processes described herein. The computer system 600 can be connected (e.g., networked) to other machines in a LAN, an intranet, an extranet, or the Internet. Although only a single device is shown, the computer system 600 may include any device collection that executes a set (or multiple sets) of instructions individually or jointly to perform any one or more of the methods discussed herein. Therefore, any reference to a computer system, a computing system, a computer device, a computing device, a control system, a control unit, an electronic control unit (ECU), a processor device, a processing circuit, etc. in the present disclosure and / or claims includes a reference to one or more such devices for executing a set (or multiple sets) of instructions individually or jointly to perform any one or more of the methods discussed herein. For example, the control system may include a single control unit or multiple control units connected to each other or otherwise communicatively coupled, so that any executed functions can be distributed between the control units as needed. In addition, such devices can communicate with each other or with other devices through various system architectures (such as directly or via a controller area network (CAN) bus, etc.).

[0060] The computer system 600 may include at least one computing device or electronic device that can include firmware, hardware and / or execute software instructions to implement the functionality described herein. The computer system 600 may include a processing circuit system 602 (e.g., a processing circuit system including one or more processor devices or control units), a memory 604, and a system bus 606. The computer system 600 may include at least one computing device with a processing circuit 602. The system bus 606 provides an interface for system components (including but not limited to the memory 604 and the processing circuit 602). The processing circuit 602 may include any number of hardware components for performing data or signal processing or for executing computer code stored in the memory 604. The processing circuit system 602 may include, for example, a general-purpose processor, a special-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), a circuit containing a processing component, a group of distributed processing components, a group of distributed computers configured for processing, or other programmable logic devices designed to perform the functions described herein, discrete gate or transistor logic, discrete hardware components, or any combination thereof. The processing circuit system 602 may also include computer executable code that controls the operation of the programmable device.

[0061] The system bus 606 can be any of several types of bus structures, which can be further interconnected to a memory bus (with or without a memory controller), a peripheral bus, and / or a local bus using any of a variety of bus architectures. The memory 604 can be one or more devices for storing data and / or computer code to complete or facilitate the methods described herein. The memory 604 can include a database component, an object code component, a script component, or other types of information structures for supporting various activities herein. Any distributed or local memory device can be used with the systems and methods of the present specification. The memory 604 can be communicatively connected to the processing circuit 602 (e.g., via a circuit or any other wired, wireless, or network connection) and can include computer code for performing one or more processes described herein. The memory 604 may include nonvolatile memory 608 (e.g., read-only memory (ROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), etc.) and volatile memory 610 (e.g., random access memory (RAM)) or any other medium that can be used to carry or store desired program code in the form of machine-executable instructions or data structures and that can be accessed by a computer or other machine having the processing circuit 602. A basic input / output system (BIOS) 612 may be stored in the nonvolatile memory 608 and may include the basic routines that help to transfer information between elements within the computer system 600.

[0062] The computer system 600 may also include or be coupled to non-transitory computer-readable storage media such as storage device 614, which may include, for example, an internal or external hard disk drive (HDD) (e.g., enhanced integrated drive electronics (EIDE) or serial advanced technology attachment (SATA)), a HDD for storage (e.g., EIDE or SATA), flash memory, etc. The storage device 614 and other drives associated with computer-readable and computer-usable media may provide non-volatile storage of data, data structures, computer-executable instructions, etc.

[0063] The hard-coded or soft-coded computer code may be provided in the form of one or more modules. The module may be implemented as software and / or hard-coded in the circuit to implement the functions described herein in whole or in part. The module may be stored in a storage device 614 and / or a volatile memory 610 that may include an operating system 616 and / or one or more program modules 618. All or part of the examples disclosed herein may be implemented as a computer program 620 stored on a temporary or non-temporary computer-available or computer-readable storage medium (e.g., a single medium or multiple media) such as a storage device 614, which includes complex programming instructions (e.g., complex computer-readable program code) that cause the processing circuit 602 to perform the actions described herein. Therefore, the computer-readable program code of the computer program 620 may include software instructions for implementing the functions of the examples described herein when executed by the processing circuit 602. In some examples, storage device 614 may be a computer program product (e.g., a readable storage medium) having computer program 620 stored thereon, wherein at least a portion of computer program 620 may be loadable (e.g., loaded into a processor) for implementing functionality of the examples described herein when executed by processing circuitry 602. Processing circuitry 602 may serve as a controller or control system of computer system 600 for implementing the functionality described herein.

[0064] The computer system 600 may include an input device interface 622 configured to receive input and selections to be transmitted to the computer system 600 when executing instructions, such as from a keyboard, mouse, touch-sensitive surface, voice commands, etc. Such input devices can be connected to the processor circuit 602 through an input device interface 622 coupled to the system bus 606, but can be connected through other interfaces (such as a parallel port, an Institute of Electrical and Electronics Engineers (IEEE) 1394 serial port, a universal serial bus (USB) port, an IR interface, etc.). The computer system 600 may include an output device interface 624, which is configured to forward output to a display, a video display unit (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)). The computer system 600 may include a communication interface 626 suitable for communicating with a network as appropriate or required.

[0065] The operational actions described in any exemplary aspect of this article are described to provide examples and discussions. These actions can be performed by hardware components, can be embodied in machine executable instructions so that a processor performs these actions, or can be performed by a combination of hardware and software. Although a specific order of method actions can be shown or described, the order of actions can be different. In addition, two or more actions can be performed simultaneously or partially simultaneously.

[0066] The terms used herein are only used for the purpose of describing specific aspects and are not intended to limit the present disclosure. As used herein, unless the context clearly indicates otherwise, the singular forms "one", "a kind of" and "the" are intended to also include plural forms. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items. It should also be understood that the terms "include" and / or "comprising" when used herein indicate the presence of stated features, integers, actions, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, actions, steps, operations, elements, components and / or their groups.

[0067] It should be understood that although the terms first, second, etc. can be used to describe various elements in this article, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, without departing from the scope of the present disclosure, the first element can be referred to as the second element, and similarly, the second element can be referred to as the first element.

[0068] Relative terms such as "below" or "above" or "upper" or "lower" or "horizontal" or "vertical" may be used herein to describe the relationship of one element to another element, as shown in the figures. It should be understood that these terms and those discussed above are intended to cover different device orientations in addition to the orientations depicted in the figures. It should be understood that when an element is referred to as being "connected" or "coupled" to another element, the element may be directly connected or directly coupled to the other element, or there may be intermediate elements. In contrast, when an element is referred to as being "directly connected to" or "directly coupled to" another element, there are no intermediate elements.

[0069] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those commonly understood by those skilled in the art to which the present disclosure belongs. It should also be understood that, unless otherwise clearly defined herein, the terms used herein should be interpreted as meanings consistent with their meanings in the context of this specification and the relevant art, and should not be interpreted in an idealized or overly formal sense.

[0070] It should be understood that the present disclosure is not limited to the aspects described above and shown in the accompanying drawings; rather, those skilled in the art will recognize that many changes and modifications may be made within the scope of the present disclosure and the appended claims. In the drawings and description, various aspects have been disclosed for illustrative purposes only and not for limiting purposes, and the scope of the disclosure is set forth in the appended claims.

Claims

1. A computer system (130, 140) for a heavy vehicle (100) comprising a fuel cell system (111) and an electrical energy storage system ESS (112, 121), wherein: The computer system (130, 140) includes a processing circuit configured to: identifying (S1) a downhill portion (C) of a journey to be performed by the heavy vehicle (100), determining (S2) at least two candidate routes (R1, R2) leading from a starting position (A) along the trip to a starting point (B) of the downhill portion (C) of the trip, predicting (S3) the state of energy SoE of the ESS at the starting point (B) of the downhill portion (C) for each candidate route (R1, R2), and A suggested route is selected (S4) from the candidate routes (R1, R2) based at least in part on the predicted SoE of each candidate route and based on an estimated amount of energy regenerated by traversing the downhill portion (C) of the trip.

2. The computer system (130, 140) of claim 1, wherein: The heavy vehicle (100) comprises a fuel cell system (111) arranged to pre-charge (S0) the ESS (112, 121) prior to an uphill portion of a journey to be traversed by the heavy vehicle (100).

3. The computer system (130, 140) according to claim 1 or 2, wherein: The processing circuit is configured to predict the SoE of the ESS (112, 121) at least in part by considering (S31) predicted fuel cell charging operations along each candidate route (R1, R2).

4. The computer system (130, 140) of any preceding claim, wherein: The processing circuit is configured to predict (S32) the SoE of the ESS (112, 121) at the starting point (B) of the downhill portion (C) for each candidate route (R1, R2) at least in part by identifying an uphill portion along the candidate route (R1, R2).

5. The computer system (130, 140) of any preceding claim, wherein: The processing circuit is configured to implement a digital twin of the energy system of the heavy vehicle and predict (S33) the SoE of the ESS at the starting point (B) of the downhill portion (C) for each candidate route (R1, R2) based at least in part on the digital twin.

6. The computer system (130, 140) of any preceding claim, wherein: The processing circuit is configured to receive (S34) pre-recorded SoE curve data for at least a portion of the trip from an onboard data storage device and / or from a remote server (170).

7. The computer system (130, 140) of claim 6, wherein: The processing circuit is configured to predict (S341) the SoE of the ESS at the starting point (B) of the downhill portion (C) for each candidate route (R1, R2) based at least in part on the pre-recorded SoE curve data.

8. The computer system (130, 140) of any preceding claim, wherein: The processing circuit is configured to select (S41) the suggested route from the candidate routes (R1, R2) based at least in part on an energy storage capacity of the ESS (112, 121).

9. The computer system (130, 140) of claim 8, wherein: The processing circuit is configured to determine (S411) a present energy storage capacity of the ESS (112, 121) based at least in part on an ambient temperature.

10. The computer system (130, 140) of any preceding claim, wherein: The heavy vehicle (100) comprises an energy dissipation device (113), wherein the processing circuit is configured to select (S42) the suggested route from the candidate routes (R1, R2) based at least in part on an energy dissipation capability of the energy dissipation device (113).

11. The computer system (130, 140) of claim 10, wherein: The processing circuit is configured to determine (S421) a current energy dissipation capacity of the energy dissipation device (113) based at least in part on a current temperature of the energy dissipation device (113).

12. The computer system (130, 140) of any preceding claim, wherein: The processing circuit is configured to select (S43) the suggested route from the candidate routes (R1, R2) based at least in part on a retarding braking capability and / or a cooling capability of a service brake system of the heavy vehicle (100).

13. The computer system (130, 140) of any preceding claim, wherein: The processing circuit is configured to suggest (S5) stopping ESS discharge along a route before the downhill portion (C) when no candidate route meets the SoE acceptance criteria at the starting point (B) of the downhill portion (C).

14. The computer system (130, 140) of any preceding claim, wherein: The starting position is the current position of the heavy vehicle (100).

15. The computer system (130, 140) of any preceding claim, wherein: The processing circuit is configured to record a SoE curve along the trip based on the position of the heavy vehicle (100).

16. The computer system (130, 140) of claim 15, wherein: The processing circuit is configured to transmit (150) the recorded SoE curve along the trip to an onboard data storage device and / or a remote server (170).

17. A heavy vehicle (100) comprising a computer system (130, 140) according to any preceding claim.

18. A computer-implemented method performed by a computer system (130, 140) in a heavy vehicle (100) comprising a fuel cell system (111) and an electrical energy storage system ESS (112, 121), the method comprising: identifying (S1) by processing circuitry of the computer system a downhill portion (C) of a journey to be undertaken by the heavy vehicle (100), determining (S2) by the processing circuit at least two candidate routes (R1, R2) leading from a starting position (A) along the trip to a starting point (B) of the downhill portion (C) of the trip, predicting (S3) by the processing circuit for each candidate route (R1, R2) the state of energy SoE of the ESS at the starting point (B) of the downhill portion (C), and A suggested route is selected (S4) by the processing circuit from the candidate routes (R1, R2) based at least in part on the predicted SoE for each candidate route and based on an estimated amount of energy regenerated by traversing the downhill portion (C) of the trip.

19. A computer program product comprising program code for performing the method according to claim 18 when the program code is executed by the processing circuit.

20. A non-transitory computer-readable storage medium comprising instructions that, when executed by the processing circuit, cause the processing circuit to perform the method of claim 18.

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