MOCAST 2021

The 10th International Conference on Modern Circuit and System Technologies on Electronics and Communications (MOCAST 2021) will take place in Thessaloniki, Greece, from July 5th to July 7th, 2021. The MOCAST technical program includes all aspects of circuit and system technologies, from modeling to design, verification, implementation, and application. This Special Issue presents extended versions of top-ranking papers in the conference. The topics of MOCAST include:Analog/RF and mixed signal circuits;Digital circuits and systems design;Nonlinear circuits and systems;Device and circuit modeling;High-performance embedded systems;Systems and applications;Sensors and systems;Machine learning and AI applications;Communication; Network systems;Power management;Imagers, MEMS, medical, and displays;Radiation front ends (nuclear and space application);Education in circuits, systems, and communications

Model-based powertrain design and control system development for the ideal all-wheel drive electric vehicle

The transfer case based all-wheel drive electric vehicle (TCAWDEV) and dual-axle AWDEV have been investigated to balance concerns about energy consumption, drivability and stability of vehicles. However, the mentioned powertrain architectures have the torque windup issue or the wheel skidding issue. The torque windup is an inherent issue of mechanical linked all-wheel drive systems. The hydraulic motor-based or the electric motor-based ideal all-wheel drive powertrain can provide feasible solutions to the mentioned issues. An ideal AWDEV (IAWDEV) powertrain architecture and its control schemes were proposed by this research; the architecture has four independent driving motors in powertrain. The IAWDEV gives more control freedoms to implement active torque controls and traction mode controls. In essence, this research came up with the distributed powertrain concept, and developed control schemes of the distributed powertrain to replace the transfer case and differential devices. The study investigated the dual-loop motor control, the hybrid sliding mode control (HSMC) and the neural network predictive control to reduce energy consumption and achieve better drivability and stability by optimizing the torque allocation of each dependent wheel. The mentioned control schemes were respectively developed for the anti-slip, differential and yaw stability functionalities of the IAWDEV powertrain. This study also investigated the sizing method that the battery capacity was estimated by using cruise performance at 3% road grade. In addition, the model-based verification was employed to evaluate the proposed powertrain design and control schemes. The verification shows that the design and controls can fulfill drivability requirements and minimize the existing issues, including torque windup and chattering of the slipping wheel. In addition, the verification shows that the IAWDEV can harvest around two times more energy while the vehicle is running on slippery roads than the TCAWDEV and the dual-axle AWDEV; the traction control can achieve better drivability and lower energy consumption than mentioned powertrains; the mode control can reduce 3% of battery charge depleting during the highway driving test. It also provides compelling evidences that the functionalities achieved by complicated and costly mechanical devices can be carried out by control schemes of the IAWDEV; the active torque controls can solve the inherent issues of mechanical linked powertrains; the sizing method is credible to estimate the operation envelop of powertrain components, even though there is some controllable over-sizing

Tuning the Computational Effort: An Adaptive Accuracy-aware Approach Across System Layers

This thesis introduces a novel methodology to realize accuracy-aware systems, which will help designers integrate accuracy awareness into their systems. It proposes an adaptive accuracy-aware approach across system layers that addresses current challenges in that domain, combining and tuning accuracy-aware methods on different system layers. To widen the scope of accuracy-aware computing including approximate computing for other domains, this thesis presents innovative accuracy-aware methods and techniques for different system layers. The required tuning of the accuracy-aware methods is integrated into a configuration layer that tunes the available knobs of the accuracy-aware methods integrated into a system