Thesis: Process for deriving and optimizing vehicle dynamics models

Volvo Business Services AB / Maskiningenjörsjobb / Göteborg
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Background of thesis project

The future of vehicle automation heavily relies on vehicle simulations for the upbringing of different autonomous applications, whether it is related to path planning, motion planning or control. The development of any such functionality depends on the continuous regression testing of the system. The backbone of vehicle simulations is a vehicle model upon which the application is tested. Since the development happens at different stages, there are different requirements on vehicle models which lead to different vehicle model fidelities. High fidelity models are generally used for off-line simulations and in fast computing rigs where the high-fidelity model represents possible dynamics and physics of a real vehicle. High fidelity models are validated against measured data and used as a reference for validation of simpler, low fidelity models. Such lower fidelity models are superior regarding the computational cost but are rather application specific, hence more low fidelity models are needed to cover the necessary applications. In [1], a process for optimizing Modelica [2] models using a CasADi [3] framework and FMI standard [5] is proposed. The process links defining model applications to model optimization and validation. Such processes are important for the continuous validation of vehicle models within the vehicle modeling team, and important for growing the model garage provided by that team.

Suitable background
Of students
We are looking for highly motivated master thesis students with a genuine interest in system dynamics, mechanics and mathematics. Profiles of interest are mechanical engineering, mathematics, mechatronics, systems and controls
Profound in English, both verbally and written
Meritorious: knowledge of Modelica

Description of thesis work

Aim

Using the available tools within the Volvo group organization, design two process workflows and methods that allow for the automatic generation and validation of low fidelity vehicle models. The generated models are to be shared as FMUs and integrated in the plurality of virtual environments within V.A.S.
Scope
An existing "high-fidelity" vehicle model developed in Modelica and shared as an FMU is envisioned.
Methods for deriving low fidelity models and model optimization
Integrating the designed process with existing workflows in V.A.S.
Used language/technologies: Modelica [2], Python [4], FMI [5], ModeFrontier [6]

Tasks
Literature review on model design, optimization, and validation.
Develop and propose automated process/es
Document and report in English
Present results

References
Takkoush, Mohamed, (2022), "Optimization of a Tractor-Semitrailer Vehicle Model", Modelon Innovate, Stockholm
Modelica, https://modelica.org/modelicalanguage.html
Joel A E Andersson, Joris Gillis, Greg Horn, James B Rawlings, and Moritz Diehl. CasADi - A software framework for nonlinear optimization and optimal control. Mathematical Programming Computation, 11(1):1-36, 2019.
Python, https://www.python.org/about/
Functional Mock-up Interface, https://fmi-standard.org/
modeFRONTIER, https://engineering.esteco.com/modefrontier/

Thesis Level: Master

Language: English

Starting date: September 4, 2023

Number of students: 2

Tutor

Edo Drenth, Simulation and Analysis Engineer
Mohamed Takkoush, Vehicle Dynamics Analyst, +46 765537590

Kindly note that due to GDPR, we will not accept applications via mail. Please use our career site.

Så ansöker du
Sista dag att ansöka är 2023-12-31
Klicka på denna länk för att göra din ansökan

Omfattning
Detta är ett heltidsjobb.

Arbetsgivare
Volvo Business Services AB (org.nr 556029-5197)
405 08  GÖTEBORG

Arbetsplats
Volvo Group

Jobbnummer
8031907

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