Integrated digital-twin development to support infrastructure design, decision making, and additional operational features for various charging applications
Department(s)
Mechanical Engineering
Reference number
V35.5457
Job description
In order to achieve the climate objectives, national and international developments are increasingly required in the field of sustainable transport. With innovative battery technology as a core component of this transition, the proposed Green Transport Delta (GTD) – Electrification project focuses on establishing and perpetuating an integrated approach to R&D in the Dutch battery value chain. The main goals of the GTD project are to accelerate the transition to climate-neutral mobility, promote a circular economy, and further develop a strong Dutch (manufacturing) industry that is internationally competitive and contributes to the future earning capacity of the Netherlands.
In this context, the overall aim of our work package (WP) integral upscaling of charging infrastructure with partners is to develop an intelligent and bi-directional energy system based on a modular charging platform with a capacity of one megawatt, integrated with local energy storage (battery energy storage system, V2G) and renewable energy sources from both fixed sources (solar parks/solar roofs) or dynamic sources (PV-on-trailer/in-vehicle-PV). The tasks specified by the project partners for this purpose can be divided into R&D, verification, and validation activities. The WP includes the development of both hardware (such as the modular, bi-directional one megawatt charger, and the elements for integrations with distributed energy resources, vehicle, and trailer) and software (such as the digital twins, optimization tools and software for energy planning and fleet planning). Ultimately, these parts together form the bi-directional energy system that can be controlled based on many internal and external parameters.
Figure 1: Agent-based simulation environmentThe PhD project specifically supports in the task related to system optimization for design and operation. The purpose of this task is twofold: First, a process is defined and to design a detailed arrangement of a bi-directional energy system for charging applications and to support this process based on a model-based simulation environment (task a). Particularly with complex issues such as the design of public charging plazas, charging solutions along (inter-)national corridors and locations with a high degree of congestion on the grid, it will be necessary to evaluate design plans based on supporting simulation environments/tools by calculation (see the agent-based model example in Figure 1). The second goal of this task is to increase the energy and cost efficiency of operating this charging infrastructure based on digital twins and fleet planning. The basis for this holistic application is a common fleet planning tool, which is extended with a predictive model environment that considers current information from the vehicles, grid load, available (renewable) energy, and current energy prices, identifying potential problems and proposing improvements where possible. Ultimately, we aim to develop a working example of such a holistic application for fleet planning and energy planning (task b). Subtasks under these tasks a. and b. are:
Figure 2: Electric airplanes as use casea.1 Definition and dissemination step-by-step plan for setting up a fast-charging infrastructure;
a.2 Specification of a simulation tool for charging infrastructure scenario analysis;
a.3 Design and implementation of a simulation tool for charging infrastructure scenario analysis;
a.4 Validation of the simulation tools based on use cases (a testing ground for energy needs in relation to fleet planning at a distribution center, public charging, charging at a small airport, e.g., see Figure 2).
b.1 Identification of the required services and associated information needs for holistic dynamic journey planning;
b.2 Specification and dissemination of extensions to existing standards:
b.3 Design and implementation of a dynamic route planning tool;
b.4 Validation, evaluation, and demonstration of the holistic dynamic route planning tool.
Job requirements
Talented, enthusiastic candidates with excellent analytical and communication skills are encouraged to apply. A MSc degree (or equivalent) in Mechanical, Electrical Engineering, Systems & Control or a related discipline is required, as well as a strong background in system engineering, optimization, and optimal control methods. Experience and interests in transportation engineering, energy systems, modelling of powertrain systems, automotive technology, digital twin technology, agent-based modelling, system design and control are of benefit.
Conditions of employment
We offer a challenging position for four years in a highly motivated team at a dynamic and ambitious university. You will be part of a highly profiled multidisciplinary collaboration where expertise of a variety of disciplines comes together. The TU/e is in one of the smartest regions of the world and part of the European technology hotspot ‘Brainport Eindhoven’; well-known because of many high-tech industries and start-ups. A place to be for talented scientists!
- A meaningful job in a dynamic and ambitious university with the possibility to present your work at international conferences.
- A full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months.
- To develop your teaching skills, you will spend 10% of your employment on teaching tasks.
- To support you during your PhD and to prepare you for the rest of your career, you will make a Training and Supervision plan and you will have free access to a personal development program for PhD students (PROOF program ).
- A gross monthly salary and benefits (such as a pension scheme, pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labor Agreement for Dutch Universities.
- Additionally, an annual holiday allowance of 8% of the yearly salary, plus a year-end allowance of 8.3% of the annual salary.
- Should you come from abroad and comply with certain conditions, you can make use of the so-called ‘30% facility’, which permits you not to pay tax on 30% of your salary.
- A broad package of fringe benefits, including an excellent technical infrastructure, moving expenses, and savings schemes.
- Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.
Information and application
More information about the project can be obtained from dr. T. Hofman, e-mail: t.hofman[at]tue.nl; dr. M. Salazar, m.u.r.salazar[at]tue.nl; ir. A. Hoekstra, e-mail: a.e.hoekstra[at]tue.nl.
For information about terms of employment, click here or contact HR Services, email: HRServices.Gemini[at]tue.nl.
Please visit www.tue.nl/jobs to find out more about working at TU/e!
Application
We invite you to submit a complete application by using the 'apply now'-button on this page.
The application should include a:
- a cover letter (stating personal goal and research interests connecting to one or more of the topics defined above).
- a complete Curriculum Vitae (including transcript of records and a list of publications if any).
- contact information of three reference persons.
We look forward to your application and will screen it as soon as we have received it. Screening will continue until the position has been filled.
We do not respond to applications that are sent to us in a different way.
Please keep in mind you can upload only 5 documents up to 2 MB each. If necessary, please combine files.
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