A STUDY OF REGENERATIVE BRAKING SYSTEM (RBS) INVOLVING MODIFIED BRAKE PEDAL FOR RETROFIT CONVERSION OF HYBRID ELECTRIC VEHICLE (HEV)

Regenerative braking system has always been a very important feature in all hybrid and full electric vehicles since it helps to improve on fuel economy, as well as conserve energy efficiency. Unlike conventional vehicles which apply the friction brake system and contribute to the loss of the kinetic energy in the form of heat energy and friction, regenerative braking can conserve the energy lost during braking. Issue is addressed as to why this project is carried out. There is a lack of regenerative braking performance study for a bench-testing prototyping stage in retrofit conversion of hybrid electric vehicles. Also, the current solution to implement a regenerative braking system in existing vehicle part is costly. In this project, alternatives are first, explored to design brake pedal assembly to detect brake pedal movement for regenerative braking. In order to achieve this, a linear potentiometer is selected. This is followed with the design of a voltage follower circuit to produce stable output voltage to the motor controller. Then, configuration of the circuitry to the motor controller is learnt and set-up. Last part of the step covers the monitoring and experimentation of the performance for regenerative current by using the lab equipment. The bench-testing is done in free or zero-load condition. Results obtained showed a very little regenerative current being fed back into the battery when the brake pedal is exerted at its maximum, with respect to different motor speed run. Further work can be carried out to test the actual regenerative performance when the prototype is fully mounted into the vehicle

A STUDY OF REGENERATIVE BRAKING SYSTEM (RBS) INVOLVING MODIFIED BRAKE PEDAL FOR RETROFIT CONVERSION OF HYBRID ELECTRIC VEHICLE (HEV)

Regenerative braking system has always been a very important feature in all hybrid and full electric vehicles since it helps to improve on fuel economy, as well as conserve energy efficiency. Unlike conventional vehicles which apply the friction brake system and contribute to the loss of the kinetic energy in the form of heat energy and friction, regenerative braking can conserve the energy lost during braking. Issue is addressed as to why this project is carried out. There is a lack of regenerative braking performance study for a bench-testing prototyping stage in retrofit conversion of hybrid electric vehicles. Also, the current solution to implement a regenerative braking system in existing vehicle part is costly. In this project, alternatives are first, explored to design brake pedal assembly to detect brake pedal movement for regenerative braking. In order to achieve this, a linear potentiometer is selected. This is followed with the design of a voltage follower circuit to produce stable output voltage to the motor controller. Then, configuration of the circuitry to the motor controller is learnt and set-up. Last part of the step covers the monitoring and experimentation of the performance for regenerative current by using the lab equipment. The bench-testing is done in free or zero-load condition. Results obtained showed a very little regenerative current being fed back into the battery when the brake pedal is exerted at its maximum, with respect to different motor speed run. Further work can be carried out to test the actual regenerative performance when the prototype is fully mounted into the vehicle

Effects of anthropogenic activities on the heavy metal levels in the clams and sediments in a tropical river

The present study aimed to assess the effects of anthropogenic activities on the heavy metal levels in the Langat River by transplantation of Corbicula javanica. In addition, potential ecological risk indexes (PERI) of heavy metals in the surface sediments of the river were also investigated. The correlation analysis revealed that eight metals (As, Co, Cr, Fe, Mn, Ni, Pb and Zn) in total soft tissue (TST) while five metals (As, Cd, Cr, Fe and Mn) in shell have positively and significantly correlation with respective metal concentration in sediment, indicating the clams is a good biomonitor of the metal levels. Based on clustering patterns, the discharge of dam impoundment, agricultural activities and urban domestic waste were identified as three major contributors of the metals in Pangsun, Semenyih and Dusun Tua, and Kajang, respectively. Various geochemical indexes for a single metal pollutant (geoaccumulation index (I geo), enrichment factors (EF), contamination factor (C f) and ecological risk (Er)) all agreed that Cd, Co, Cr, Cu, Fe, Mn, Ni and Zn are not likely to cause adverse effect to the river ecosystem, but As and Pb could pose a potential ecological risk to the river ecosystem. All indexes (degree of contamination (C d), combined pollution index (CPI) and PERI) showed that overall metal concentrations in the tropical river are still within safe limit. River metal pollution was investigated. Anthropogenic activities were contributors of the metal pollution. Geochemical indexes showed that metals are within the safe limit

Ensemble-Based Out-of-Distribution Detection

To design an efficient deep learning model that can be used in the real-world, it is important to detect out-of-distribution (OOD) data well. Various studies have been conducted to solve the OOD problem. The current state-of-the-art approach uses a confidence score based on the Mahalanobis distance in a feature space. Although it outperformed the previous approaches, the results were sensitive to the quality of the trained model and the dataset complexity. Herein, we propose a novel OOD detection method that can train more efficient feature space for OOD detection. The proposed method uses an ensemble of the features trained using the softmax-based classifier and the network based on distance metric learning (DML). Through the complementary interaction of these two networks, the trained feature space has a more clumped distribution and can fit well on the Gaussian distribution by class. Therefore, OOD data can be efficiently detected by setting a threshold in the trained feature space. To evaluate the proposed method, we applied our method to various combinations of image datasets. The results show that the overall performance of the proposed approach is superior to those of other methods, including the state-of-the-art approach, on any combination of datasets

A 1.25V DIRECT-CONVERSION CMOS TRANSMITTER FRONT-END FOR 900MHz ZIGBEE APPLICATIONS

This paper presents a very low power direct-conversion up-mixer and driver amplifier. The designed mixer is based on the typical Gilbert-cell, and the driver amplifier uses a folded cascode topology to improve the linearity under the low supply voltage. The fabricated up-mixer shows 5.5dB of conversion gain and 7.5dBm of output IP3, and the driver amplifier shows 17dB of power gain and 12dBm of output IP3. The up-mixer and driver amplifier consume 4.5mA and 2mA from 1.25V supply, respectively. 1

Effect of Hole Shift on Threshold Characteristics of GaSb-Based Double-Hole Photonic-Crystal Surface-Emitting Lasers

Photonic-crystal (PC) surface-emitting lasers (SELs) with double-hole structure in the square-lattice unit cell were fabricated on GaSb-based type-I InGaAsSb/AlGaAsSb heterostructures. The relative shift of two holes was varied within one half of the lattice period. We measured the lasing wavelengths and threshold pumping densities of 16 PC-SELs and investigated their dependence on the double-hole shift. The experimental results were compared to the simulated wavelengths and threshold gains of four band-edge modes. The measured lasing wavelength did not exhibit switching of band-edge mode; however, the calculated lowest threshold mode switched as the double-hole shift exceeded one quarter of the lattice period. The identification of band-edge lasing mode revealed that modal gain discrimination was dominated over by its mode wavelength separation