Posted 14 days ago
Intern - Energy Management System Development & Battery Optimization
AI Summary
Support the development of Energy Management Systems and battery optimization algorithms for large-scale battery energy storage, including control strategy design, optimization-based scheduling, AI/ML forecasting, and system validation using simulation and real datasets.
About this role
Huawei's Ohm Research Center (Nuremberg) is responsible for Advanced Technology Research, Architecture Evolution Design and Strategic Technology Planning.
Huawei Digital Power is a business unit within Huawei that provides Enterprise & Industry customers, products and solutions like clean power generation, transportation electrification, site power facilities, data center facilities, and embedded power. Huawei Digital Power is committed to integrate Digital and Power Electronics technologies to provide customers with high-quality, energy-efficient, green, and low-carbon power electronics products, facilitating their business success.
The Power Conversion Technology Laboratory within the Huawei's Ohm Research Center (Nuremberg) is responsible for Advanced Digital Power Technology Research, Architecture Evolution Design and Strategic Technology Planning, and plays an important role in the Huawei Digital Power business in the design and development of power converters and control systems for applications such as PV Solar & Battery Energy Storage Field, Data Centers, Electric Vehicle, and Embedded Power Supply.
We are looking for a motivated student to support our Energy Management System (EMS) development for battery energy storage applications, especially in large-scale utility and C&I contexts. The role includes utilizing high-level battery system models and controllers, advancing control functions, and validating optimization and AI-driven algorithms under real-time operating conditions.
Join us as a
Intern - Energy Management System Development & Battery Optimization (m/f/d)
Your mission
Work with and extend battery system models and controllers
Develop and test new EMS control strategies
Design, implement, and benchmark optimization-based scheduling algorithms
Compare different optimization approaches (LP/MILP/MPC/RL) and analyze the approaches performance
Contribute to AI/ML modules for forecasting and decision support
Support system validation using simulation frameworks and real or synthetic datasets
Your areas of expertise
Bachelor/Master/PhD student in Electrical Engineering, Energy Systems, Control Engineering, Computer Science, or a related field
Good understanding of renewable power/energy systems and battery operation
Solid understanding of optimization concepts to support algorithm development; AI/ML and Big Data skills are a plus
Experience with Python, Modelica or equivalent modeling and simulation environments, Linux system use experience is a plus
Experience in SoX estimation approaches (SoC/SoH/SoP/SoE) for LFP batteries is a strong plus
Familiarity with optimization or AI/ML frameworks is an advantage
Fluent in written and spoken English language
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Your rewards of working here
Our culture is characterized by innovative power and team spirit as well as the intensive exchange of knowledge and experience within our global network.
To keep your development ongoing, you will find a broad range of training opportunities. Many online and face-to-face training programs incl. language courses in German and Mandarin.
Our diverse and welcoming environment is shaped by different backgrounds and around 40 individual nationalities.
Self-responsible work in a competent, motivated and constantly growing team.
Please send your application and CV (incl. cover letter and reference letters) in English.
Huawei is a leading global information and communications technology (ICT) solutions provider. Our ICT solutions, products and services are used in more than 170 countries and regions, serving over one-third of the world's population. With 197,000 employees, Huawei is committed to develop the future information society and build a Better Connected World.
Skills
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