Jakob Andert

Professor

RWTH Aachen University

Germany

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Professor Jakob Andert is a faculty member at RWTH Aachen University in Germany. His research focuses on model predictive control, reinforcement learning, and thermal modeling in the context of electric vehicles and electric machines. Recent articles include topics such as intelligent charging strategies, real-time temperature estimation for electric motors, and the integration of deep neural networks in automotive applications.

Articles (20)

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Collaborators (6)

David Gordon

Assistant Professor

University of Alberta

CANADA

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Marius Wegener

RWTH Aachen University

GERMANY

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Julian Bedei

RWTH Aachen University

GERMANY

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Markus Eisenbarth

Chief Engineer

RWTH Aachen University

GERMANY

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Patrick Schaber

RWTH Aachen University

GERMANY

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Charles Koch

Professor

University of Alberta

CANADA

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Jakob Andert

Research Interests

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About

Articles (20)

Model Predictive Control for Charging Management Considering Mobile Charging Robots

Incorporating a Deep Neural Network into Moving Horizon Estimation for Embedded Thermal Torque Derating of an Electric Machine

Estimating the real-time temperature of a 48V permanent magnet synchronous motor using a thermal neural network

Thermal and loss modeling of scaled permanent magnet synchronous machines for automotive driving cycles

Transfer of Reinforcement Learning-Based Powertrain Controllers From Model- to Hardware-in-the-Loop

An Electric Vehicle Charging Simulation to Investigate the Potential of Intelligent Charging Strategies

Dynamic Closed-Loop Validation of a Hardware-in-the-Loop Testbench for Parallel Hybrid Electric Vehicles

A Unified Model and Flux Observer for Dual Three-Phase Electric Machines

LExCI: A framework for reinforcement learning with embedded systems

Support vector machine based emissions modeling using particle swarm optimization for homogeneous charge compression ignition engine

Multi-perspective evaluation of fuel-efficient architecture for China's plug-in hybrid electric vehicles across levels, time, and driving cycles

A review of silicon carbide MOSFETs in electrified vehicles: Application, challenges, and future development

Simulation of the Circulating Bearing Currents for Different Stator Designs of Electric Traction Machines

Cloud-Based Reinforcement Learning in Automotive Control Function Development

Centralized model‐predictive cooperative and adaptive cruise control of automated vehicle platoons in urban traffic environments

Active temperature control of electric drivetrains for efficiency increase

Engine-in-the-Loop in practical application: A sensitivity study toward the influence of test bench parameters

Dynamic measurement with in-cycle process excitation of HCCI combustion: The key to handle complexity of data-driven control?

Automated function development for emission control with deep reinforcement learning

Hybridisation Concept of Light Vehicles Utilising an Electrified Planetary Gear Set

Collaborators (6)

David Gordon

Marius Wegener

Julian Bedei

Markus Eisenbarth

Patrick Schaber

Charles Koch

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