From System Model to Operational Environment: Testing H2-Hybrid Drives for Mobile Machinery

1  Introduction

To date, mobile machinery has mostly been powered by combustion engines and contributes significantly to environmental impact in Germany [1]. Increasing environmental awareness is reflected in legislation aimed at making European mobile machinery the cleanest in the world [2]. Hybrid H2 drives with battery and fuel cell promise zero well-to-wheel emissions and therefore offer the potential to meet future climate targets. However, integrating hybrid H2 FC drives into mobile machinery presents a notable challenge due to the complex mechatronic nature of these systems.
Their development process, including verification and validation (V&V) processes, introduces substantial economic risks for manufacturers due to the inherent complexity. To handle complex product development the model-based systems engineering (MBSE) approach is already being used. For instance MBSE can be expected to accelerate verification processes [3], thereby reducing the economic risk and accelerating the market introduction of hybrid H2 FC drives for mobile machinery.
Verification as process is guided by a tool and a method [4]. The purpose of the verification process is to provide objective proof that a system meets the specified requirements. Design verification is the task of verifying design specifications against the design requirements [5].
In our ongoing Hy-FCD research project, a hybrid H2 FC drive for a mobile machine is being developed and implemented as a prototype. Central aspects of the project are the support of the development using MBSE and the V&V of the prototype design in virtual (simulation), physical-virtual (HiL test) and physical (operational) environments. The hybrid H2 FC drives’s HiL tests will be conducted on a system test bench. Machinery tests will be carried out at the FutureSite testing center [15] for operational environment tests. The following article presents our method to virtual (simulation-based) design verification for hybrid H2 FC drives in mobile machinery, utilizing an MBSE system model.
 

2  Use case: Hybrid Hydrogen Fuel Cell Drive

The approach considers an exemplary hybrid H2 FC drive of a material handler within the scope of Fig. 1. Further possible architectures can be found in the literature [16]. The purpose of the hybrid H2 FC drive is to provide mechanical power to both mechanical outputs of the slewing, working and traveling drives.

Source: MSE – RWTH Aachen University

Fig. 1: Exemplary hybrid H2 FC drive architecture

Excavators are operated very dynamically resulting in phases of high power demand and extended idling periods. For this reason, five individual measured work tasks are sequenced in such a way that a determined average power is achieved in 4 hours on average. This duty cycle is defined as a time-based load cycle of torque and speed of the two mechanical shafts.
To implement MBSE in the development projects we adapt the motego method [18-21] to the Simulink modelling language and the Matlab/Simulink System Composer tool. This approach results is a system model that includes the material handler modeled on a requirements, function, solution, and product level.
The system model initially utilized to identify suitable design parameters (such as battery size and EMS-parameters). During a optimization-based approach iteration takes place between an analysis environment and an optimizer. As a result, design variants are available. The selected, most suitable variant can then be further analyzed and might be adapted to available components on the market. These design modifications require re-verification.
 

3  Method and Results

The system sizing (design definition) as previously described produces design output specifications that must be verified against the previously formulated design requirements. In our case, this design verification is supported by the developed method depicted in Fig. 2., which is based on the existing concepts for design verification in the literature [5,6,23,24].

Source: MSE – RWTH Aachen University

Fig. 2: Method for design verification

The method for design verification is divided into three stages:

  1. Planning Stage
  2. Execution Stage
  3. Reporting Stage

In the following, the developed method is applied to the use case (Fig. 1). For this, the developed system model, that contains the design output specifications is used. For instance, the design is verified against the "Tank Range" requirement, which states that “For a 4-hour work shift, the remaining tank pressure must be at least 50 bar”.

During the planning stage a test case is set up and corresponding test case attributes are defined and linked to elements of the system model (Fig. 3). The executed design verification in our use case contains e.g. the following attributes: A requirement to be verified which in our case is the "Tank range" design requirement provided from the requirement level of system model. As System Scope that is carried out during simulation the entire hybrid H2 FC drive of the material handler from the tank up to the shafts of the electric motors is selected. The set of design output specifications have been adapted to the values of market-available components. The values are available in a parameter set that is stored in the respective test case (Fig. 3, Parameter Overrides). In addition to the design variables, further parameter inputs are required for the initialization and execution of the system scope. These are parameters to describe the initial state of the system as well as a parameter set to describe interactions of the system with the environment. Secondly are primarily the load cycles of the two mechanical output shafts. The necessary parameters are stored as a data set in the system model and deposited with the test case (Fig. 3, Inputs). The Success criteria contain quantifiable test conditions for assessing the test outcome. In this case, the quantifiable threshold value for the assessment is PTank  > 50 bar. The variable PTank is linked to the respective state variable of the system model (Fig. 3, Success Criteria).

Source: MSE – RWTH Aachen University

Fig. 3: Implementation view of the test case

The test is executed automatically in the execution stage, based on the planning stage and the created test case. At the start of the simulation, the scope is parameterized according to the design output specifications. The conditions of use from the test case are applied to the system inputs. A signal of the model state linked to the success criterion is generated during simulation for documentation purposes. The tank pressure model state is continuously compared to the success criterion (PTank  > 50 bar), and the outcome is documented. This generates a statement about the design verification against the linked requirement.
The purposes and therefore also the reporting of verification vary greatly. In this simulation, all test settings are automatically exported, enabling the reproduction and variation of executed tests as required. Additionally, automated documentation of occurred errors and test results can be generated.

4  Discussion

We have presented a method for design verification, applied to a hybrid H2 FC drive use case. The method consists of three stages and evaluates whether the design output specifications meet the design requirements, using an established MBSE system model. To illustrate the application of the method, we provide an example involving a tank range requirement: The data from the system model was transformed and used into test cases for simulation-based testing. The test outcomes were measured against predetermined success criteria to document compliance with the requirement.
The aim of our work is to contribute to the application of V&V within MBSE for the development of mobile machinery. We have developed a method that leverages the MBSE system model to ensure comprehensive linking of development data for design verification. We expect that the resulting traceability will enhance the reproducibility of verification processes, thereby reducing the frequency of errors. Any changes in requirements and design can be automatically considered in the test cases. Automatic adaptation and execution of test cases can be expected to save time during development.
The ongoing project aims to further develop the hybrid H2 FC drive and initially test it on a system test bench. Subsequently, the drive will be integrated into the material handler, which then is tested in operational environment at the FutureSite testing center. We will explore the necessary extensions of the method to incorporate additional verification techniques, such as system test bench tests and operational environment tests.
 

5  Acknowledgment

The project is funded by the Federal Ministry for Economic Affairs and Climate Action of Germany (BMWK), grant number 03EN5027I.

6  References

[1] Aktualisierung der Modelle TREMOD/TREMOD-MM für die Emissionsberichterstattung 2020.

[2] Regulation (EU) 2016/1628 of the European Parliament and of the Council of 14 September 2016 on requirements relating to gaseous and particulate pollutant emission limits and type-approval for internal combustion engines for non-road mobile machinery, amending Regulations (EU) No 1024/2012 and (EU) No 167/2013, and amending and repealing Directive 97/68/EC (Text with EEA relevance).

[3] ISO, ISO/IEC/IEEE 15288:2023: Systems and software engineering — System life cycle processes.

[4] ISO, ISO/IEC/IEEE 24621:2023: Systems and Software engineering — Methods and tools for model-based systems and software engineering.

[5] T. Davis, INCOSE Guide to Verification and Validation.

[6] Lou Wheatcraft, Wheatland Consulting, LLC, INCOSE Needs and Requirements Manual.

[7] Software and Systems Engineering Standards Committee of the IEEE Computer Society, IEEE Std 1012-2016 (Revision of IEEE Std 1012-2012/ Incorporates IEEE Std 1012- 2016/Cor1-2017): IEEE Standard for System, Software, and Hardware Verification and Validation (2017).

[8] J. Cederbladh, A. Cicchetti, J. Suryadevara, 2023. Early Validation and Verification of System Behaviour in Model-Based Systems Engineering: A Systematic Literature Review. ACM Trans. Softw. Eng. Methodol., 3631976. doi.org/10.1145/3631976.

[9] J.B. Holladay, J. Knizhnik, K.J. Weiland, A. Stein, T. Sanders, P. Schwindt, MBSE Infusion and Modernization Initiative (MIAMI): “Hot” Benefits for Real NASA Applications, in: 2019 IEEE Aerospace Conference, Big Sky, MT, USA, IEEE, 2019, pp. 1–14.

[10] Edith Parrott, The Value of Successful MBSE Adoption, Allen, TX, USA, 2016.

[11] D. Cook, W.D. Schindel, UTILIZING MBSE PATTERNS TO ACCELERATE SYSTEM VERIFICATION, INSIGHT 20 (2017) 32–41. doi.org/10.1002/inst.12142.

[12] student, Model-Based Systems Engineering in Mobile Applications.

[13] J. Suryadevara, S. Tiwari, Adopting MBSE in Construction Equipment Industry: An Experience Report (2018) 512–521. doi.org/10.1109/APSEC.2018.00066.

[14] Johan Bergelin, Luca Berardinelli, Damir Bilic, Hugo Bruneliere, Antonio Cicchetti, MohammadHadi Dehghani, Claudio Di Sipio, James Miranda, Abbas Rahimi, Riccardo Rubei, Towards Automating the Industrial Design of CPS: The Experience of Volvo Construction Equipment.

[15] J. Odenthal, G. Jacobs, A. Kramer, J. Lipp, FutureSite - Test Center for the Development of Tomorrow's Construction Site, ATZ Heavy Duty worldw 12 (2019) 58–61. doi.org/10.1007/s41321-019-0057-z.

[16] P. Yu, M. Li, Y. Wang, Z. Chen, Fuel Cell Hybrid Electric Vehicles: A Review of Topologies and Energy Management Strategies, WEVJ 13 (2022) 172. doi.org/10.3390/wevj13090172.

[17] R.K. Ahluwalia, X. Wang, A.G. Star, D.D. Papadias, Performance and cost of fuel cells for off-road heavy-duty vehicles, International Journal of Hydrogen Energy (2022). doi.org/10.1016/j.ijhydene.2022.01.144.

[18] J.M. Berges, K. Spütz, G. Jacobs, J. Kowalski, T. Zerwas, J. Berroth, C. Konrad, Automated Identification of Valid Model Networks Using Model-Based Systems Engineering, Systems 10 (2022) 250. doi.org/10.3390/systems10060250.

[19] G. Höpfner, J. Kowalski, C. Faustmann, T. Zerwas, P. Kranabitl, S. Vafaei, G. Jacobs, H. Hick, A Classification Method for the Systematic Identification of Models and Workflows in MBSE, in: DS 119: Proceedings of the 33rd Symposium Design for X, Hamburg, 2022.

[20] G. Jacobs, C. Konrad, J. Berroth, T. Zerwas, G. Höpfner, K. Spütz, Function-Oriented Model-Based Product Development, in: D. Krause, E. Heyden (Eds.), Design Methodology for Future Products, Springer International Publishing, Cham, 2022, pp. 243–263.

[21] I. Drave, B. Rumpe, A. Wortmann, J. Berroth, G. Hoepfner, G. Jacobs, K. Spuetz, T. Zerwas, C. Guist, J. Kohl, Modeling mechanical functional architectures in SysML, in: E. Guerra (Ed.), Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings, Association for Computing Machinery, New York, 2020, pp. 79–89.

[22] ISEAFrame 2.26.0. https://isea.pages.rwth-aachen.de/framework/.

[23] Lou Wheatcraft, Wheatland Consulting, LLC, INCOSE Guide to writing requirements.

[24] Software & Systems Engineering Standards Committee of the IEEE Computer Society, IEEE Std 829-2008: IEEE Standard for Software and System Test Documentation (2008).

About the Authors

Jan de Vreeden, RWTH Aachen University, Aachen

Christian Habermehl, RWTH Aachen University, Aachen

Prof. Dr.-Ing. Georg Jacobs, RWTH Aachen University, Aachen

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