Innovative Drone Propulsion Design using Model-Based Development
Technology Category
- Analytics & Modeling - Digital Twin / Simulation
- Other - Battery
Applicable Industries
- Electronics
- Equipment & Machinery
Applicable Functions
- Product Research & Development
- Quality Assurance
Use Cases
- Virtual Prototyping & Product Testing
- Virtual Reality
Services
- Drone Operation Services
- System Integration
About The Customer
The customer in this case study is Kappa Electronics, a consulting firm specializing in motor control systems. With over 70 years of cumulative experience and a deep background in the industry, Kappa prides itself on solving complex problems while providing excellent customer service. They approach each project with the goal of doing things in a better, smarter way than anyone has done before. In this particular project, they were tasked with developing a robust motor control system for a new drone design.
The Challenge
Kappa Electronics, a consulting firm specializing in motor control systems, was approached by a customer seeking assistance with controlling the motor for a new drone design. The challenge was to develop a robust motor control system for drone applications. The control system needed to be able to handle motor frequencies ranging from 40 hertz to 2000 hertz, and perform well across a wide range of torques and parameter variations. The use of a shaft sensor to get the angle of the rotor flux with regards to the stator frame was ruled out due to cost and weight considerations. The challenge was further compounded by the need to ensure that the drone would not drop from the sky under any conditions.
The Solution
Kappa Electronics chose Altair’s solidThinking Embed® software to assist them in developing the motor control system. The software, a visual environment for model-based development of embedded systems, offered fast simulation speed, quick diagram editing, deep data input, 2D, and 3D plotting capability. This allowed Kappa to quickly develop virtual prototypes of the dynamic system, vary parameters, and verify system performance. Kappa developed an observer to estimate the flux angle by measuring the motor’s voltages and currents. They also designed a multi-mode observer structure that would dynamically reconfigure itself based on operating conditions. Kappa used Embed’s file output capabilities to generate over 600 plots of characterization data, which indicated a low angle error and suggested that the observer would not lose angle-lock, even under very adverse conditions.
Operational Impact
Quantitative Benefit
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