The Impact of Virtual Environments for Future Electric Powered-Mobility Development Using Human-in-the-Loop: Part A - Fundamental Design and Modelling

The use of virtual tools will be discussed across two complimentary chapters, Part A explores the fundamental concepts of electric vehicle systems modelling and a design procedure for human-in-the-loop virtual environments; Part B demonstrates how this architecture can be applied to assess energy optimization strategies. In Part A, this research investigates the design and implementation of simulation tools used to predict the energy consumption and strategic tool for the development of an electric vehicle. The case study used is an electric prototype race car for Ene-1 GP SUZUKA competition. Engineering effort is re-directed from physical product design, optimisation and validation to digital tools, processes and virtual testing. This virtual platform is characterised by the integration of two different simulation models—mathematical model of the electric vehicle systems represented by Matlab/Simulink, which accounts for the representation of the powertrain performance prediction that taking into account the resistance motion; and a virtual environment represented by Cruden Software, which accounts recreate topography of real world environment in a driving simulator and incorporate human driver behaviour

Filter Band Multicarrier Based Transmission Technology for Clinical EEG Signals

A transmission scheme is proposed based on filter band multicarrier (FBMC) transmission technology for clinical electroencephalogram (EEG) signals. The proposed scheme integrates binary phase shift keying (BPSK) and offset quadrature amplitude modulation (OQAM), an FBMC transmission mechanism, and low-density parity-check code (LDPC) error protection in an FBMC-based EEG mobile communication system. The proposed EEG mobile communication system employs high-speed transmission, with schemes providing significant error protection for mobile communication of clinical EEG signals requiring a stringent bit-error rate (BER). The performances of BERs and mean square errors (MSEs) of the proposed EEG mobile communication system were explored. Simulation results show that the proposed scheme is a superior transmission platform as compared to existing schemes for clinical EEG signals

The Impact of Virtual Environments for Future Electric Powered-Mobility Development Using Human-in-the-Loop: Part B - Virtual Testing and Physical Validation

Electric vehicles are increasing in popularity worldwide, and there have been numerous advances in technology to increase the energy efficiency of the vehicle and reduce the range anxiety for the user. For example, the latest electric vehicle (Tesla model S, equipped by 100kWh battery) available in the market in 2019 is able to drive around 375 miles. However, human behavior such as driving strategy is an important issue that impacts on energy optimization and ultimately vehicle range. Human behavior is rather complex and is difficult to replicate with computer algorithms. Therefore, to fully assess the impact of a particular technology, the interactions between humans, vehicle, and the environment need to be examined simultaneously, through a Human-in-the-Loop approach. In this chapter, the results of investigating a human-in-the-loop test platform, which incorporate human-driving behavior and the vehicle characteristics, are presented. In addition, this chapter analyzes a driving strategy, using a Human-in-the-Loop approach, applied to optimizing the energy usage for an electric vehicle competition

Domain Adaptation for Satellite-Borne Hyperspectral Cloud Detection

The advent of satellite-borne machine learning hardware accelerators has enabled the on-board processing of payload data using machine learning techniques such as convolutional neural networks (CNN). A notable example is using a CNN to detect the presence of clouds in hyperspectral data captured on Earth observation (EO) missions, whereby only clear sky data is downlinked to conserve bandwidth. However, prior to deployment, new missions that employ new sensors will not have enough representative datasets to train a CNN model, while a model trained solely on data from previous missions will underperform when deployed to process the data on the new missions. This underperformance stems from the domain gap, i.e., differences in the underlying distributions of the data generated by the different sensors in previous and future missions. In this paper, we address the domain gap problem in the context of on-board hyperspectral cloud detection. Our main contributions lie in formulating new domain adaptation tasks that are motivated by a concrete EO mission, developing a novel algorithm for bandwidth-efficient supervised domain adaptation, and demonstrating test-time adaptation algorithms on space deployable neural network accelerators. Our contributions enable minimal data transmission to be invoked (e.g., only 1% of the weights in ResNet50) to achieve domain adaptation, thereby allowing more sophisticated CNN models to be deployed and updated on satellites without being hampered by domain gap and bandwidth limitations

Fabrication and Photovoltaic Characteristics of Coaxial Silicon Nanowire Solar Cells Prepared by Wet Chemical Etching

Nanostructured solar cells with coaxial p-n junction structures have strong potential to enhance the performances of the silicon-based solar cells. This study demonstrates a radial junction silicon nanowire (RJSNW) solar cell that was fabricated simply and at low cost using wet chemical etching. Experimental results reveal that the reflectance of the silicon nanowires (SNWs) declines as their length increases. The excellent light trapping was mainly associated with high aspect ratio of the SNW arrays. A conversion efficiency of ∼7.1% and an external quantum efficiency of ∼64.6% at 700 nm were demonstrated. Control of etching time and diffusion conditions holds great promise for the development of future RJSNW solar cells. Improving the electrode/RJSNW contact will promote the collection of carries in coaxial core-shell SNW array solar cells

Fatigue and Fracture Behaviour of Laser Powder Bed Fusion Stainless Steel 316L: Influence of Processing Parameters

The laser powder bed fusion (L-PBF) process involves a large number of processing parameters. Extending the intricate relationship between processing and structure to mechanical performance is essential for structural L-PBF materials. The high cycle fatigue properties of L-PBF parts are very sensitive to process-induced porosities which promote premature failure through the crack initiation mechanisms. Results from this work show that for stainless steel 316L, porosity does not impinge on the high cycle fatigue properties when processing is kept within a ±30% tolerance band. In this ‘optimum’ processing region, crack initiation takes place due to defects at the solidification microstructure level. Beyond the ‘optimum’ processing region, over-melting and under-melting can lead to porosity-driven cracking and inferior fatigue resistance. In addition, regardless of the processing condition, fatigue resistance was found to follow a direct linear relationship with ductility and tensile strength in the low and high stress fatigue regimes respectively.Economic Development Board (EDB)Accepted versionThis work was supported by the Singapore Economic Development Board (EDB) Industrial Postgraduate Programme (IPP)

Post-activation Performance Enhancement after a Bout of Accentuated Eccentric Loading in Collegiate Male Volleyball Players

The purpose of this study was to investigate the benefit of post-activation performance enhancement (PAPE) after accentuated eccentric loading (AEL) compared to traditional resistance loading (TR). Sixteen male volleyball athletes were divided in AEL and TR group. AEL group performed 3 sets of 4 repetitions (eccentric: 105% of concentric 1RM, concentric: 80% of concentric 1RM) of half squat, and TR group performed 3 sets of 5 repetitions (eccentric & concentric: 85% of 1RM). Countermovement jump (CMJ), spike jump (SPJ), isometric mid-thigh pull (IMTP), and muscle soreness test were administered before (Pre) exercise, and 10 min (10-min), 24 h (24-h), and 48 h (48-h) after exercise. A two-way repeated measures analysis of variance was used to analyze the data. Peak force and rate of development (RFD) of IMTP in AEL group were significantly greater (p 0.05) groups x time. AEL seemed capable to maintain force production in IMTP, but not in CMJ and SPJ. It is recommended the use of accentuated eccentric loading protocols to overcome the fatigue