Thermal Stress Based Model Predictive Control of Power Electronic Converters in Electric Drives Applications

Power electronics is used increasingly in a wide range of application fields such as variable speed drives, electric vehicles and renewable energy systems. It has become a crucial component for the further development of emerging application fields such as lighting, more-electric aircrafts and medical systems. The reliable operation over the designed lifetime is essential for any power electronic system, particularly because the reliability of power electronics is becoming a prerequisite for the system safety in several key areas like energy, medicine and transportation. The thermal stress of power electronic components is one of the most important causes of their failure. Proper thermal management plays an important role for more reliable and cost effective energy conversion. As one of the most vulnerable and expensive components, power semiconductors, are the focus of this thesis. Active thermal control is a possibility to control the junction temperatures of power semiconductors in order to reduce the thermal stress. For this purpose the finite control-set model predictive control (FCS-MPC) is chosen. In FCS-MPC the switching vector is selected using a multi-parameter optimization that can include non-linear electric and thermal stress related models. This switching vector is directly applied to the physical system. This allows the direct control of the switching-state and the current through each semiconductor at each time instant. For cost-effective control of the thermal stress a measure for the degradation of the semiconductor's lifetime is necessary. Existing lifetime models in literature are based on the thermal cycling amplitudes and maximum values of recorded junction temperature profiles. For online estimation of the degradation, a method to detect the junction temperatures of the semiconductors during operation is designed and validated. An existing and proven lifetime model is adapted for online estimation of the thermal stress. An algorithm for the FCS-MPC is written that utilizes this model to drive the inverter with reduced stress and equalize the degradation of the semiconductors in a power module. The algorithm is demonstrated in simulation and validated in experiment. A technique to find the optimal trade-off between reduction of the thermal stress and allowing additional losses in the system is given. The effect of rotor flux variation of the machine on the junction temperatures of the driving inverter is investigated. It can be used as another parameter to control the junction temperature. This allows increasing the maximal thermal cycling amplitude that can be compensated by an active thermal controller. A suitable controller is proposed and validated in experiment. The integration of this technique into the FCS-MPC is presented

Reliability of Power Electronic Systems: An Industry Perspective

Power electronics systems are used increasingly in a wide range of application fields, such as variable-speed drives, electric vehicles, and renewable energy systems. These elements have become crucial constituents in the further development of such emerging application fields as lighting, more-electric aircraft, and medical systems [1]. Reliable operation over the designed lifetime is essential for any power electronics system [2], particularly because the dependability of power electronics is becoming a prerequisite for system safety in several key areas, e.g., energy, medicine, and transportation [3]

The importance of the intensive care unit environment in sleep-A study with healthy participants

Sleep disruption is common among intensive care unit patients, with potentially detrimental consequences. Environmental factors are thought to play a central role in ICU sleep disruption, and so it is unclear why environmental interventions have shown limited improvements in objectively assessed sleep. In critically ill patients, it is difficult to isolate the influence of environmental factors from the varying contributions of non-environmental factors. We thus investigated the effects of the ICU environment on self-reported and objective sleep quality in 10 healthy nurses and doctors with no history of sleep pathology or current or past ICU employment participated. Their sleep at home, in an unfamiliar environment ('Control'), and in an active ICU ('ICU') was evaluated using polysomnography and the Richard-Campbell Sleep Questionnaire. Environmental sound, light and temperature exposure were measured continuously. We found that the control and ICU environment were noisier and warmer, but not darker than the home environment. Sleep on the ICU was perceived as qualitatively worse than in the home and control environment, despite relatively modest effects on polysomnography parameters compared with home sleep: mean total sleep times were reduced by 48 min, mean rapid eye movement sleep latency increased by 45 min, and the arousal index increased by 9. Arousability to an awake state by sound was similar. Our results suggest that the ICU environment plays a significant but partial role in objectively assessed ICU sleep impairment in patients, which may explain the limited improvement of objectively assessed sleep after environmental interventions

Building an Aerial-Ground Robotics System for Precision Farming: An Adaptable Solution

The application of autonomous robots in agriculture is gaining increasing popularity thanks to the high impact it may have on food security, sustainability, resource use efficiency, reduction of chemical treatments, and the optimization of human effort and yield. With this vision, the Flourish research project aimed to develop an adaptable robotic solution for precision farming that combines the aerial survey capabilities of small autonomous unmanned aerial vehicles (UAVs) with targeted intervention performed by multi-purpose unmanned ground vehicles (UGVs). This paper presents an overview of the scientific and technological advances and outcomes obtained in the project. We introduce multi-spectral perception algorithms and aerial and ground-based systems developed for monitoring crop density, weed pressure, crop nitrogen nutrition status, and to accurately classify and locate weeds. We then introduce the navigation and mapping systems tailored to our robots in the agricultural environment, as well as the modules for collaborative mapping. We finally present the ground intervention hardware, software solutions, and interfaces we implemented and tested in different field conditions and with different crops. We describe a real use case in which a UAV collaborates with a UGV to monitor the field and to perform selective spraying without human intervention.Comment: Published in IEEE Robotics & Automation Magazine, vol. 28, no. 3, pp. 29-49, Sept. 202