Kash Olia

This paper presents the results of development, design and implementation of a Simultaneous Localization And Mapping (SLAM) system for autonomous real-time localization with application to Underground Transportation Infrastructure (UTI) such as tunnels. Localization is achieved in absence of any GPS or auxiliary system. The system is a necessary element of a fully autonomous platform for detection of cracks and other anomalies on the interior surfaces of tunnels and other UTI. It can be used… Show more

This paper presents the results of development, design and implementation of a Simultaneous Localization And Mapping (SLAM) system for autonomous real-time localization with application to Underground Transportation Infrastructure (UTI) such as tunnels. Localization is achieved in absence of any GPS or auxiliary system. The system is a necessary element of a fully autonomous platform for detection of cracks and other anomalies on the interior surfaces of tunnels and other UTI. It can be used for tagging of high-resolution sensor data obtained with low-cost prototype data acquisition platforms previously developed [1], [2]. Visual based SLAM has been used as the core element in an architecture also employing a Commercial Off The Shelf (COTS) ZED stereocamera from Stereolabs. To achieve real-time operation, an NVIDIA Jetson Tx2 massively parallel Graphic Processing Unit (GPU) has been used as the core computational engine employing two different software libraries. We achieved localization at 5 frames per second (fps) using ORBSLAM2 open source software library, while the much lighter but proprietary ZED SDK was able to deliver performance at nearly 60 fps. Show less

This paper is focused on the problem of Information Reconciliation (IR) for continuous variable Quantum Key Distribution (QKD). The main problem is quantization and assignment of labels to the samples of the Gaussian variables observed at Alice and Bob. Trouble is that most of the samples, assuming that the Gaussian variable is zero mean which is de-facto the case, tend to have small magnitudes and are easily disturbed by noise. Transmission over longer and longer distances increases the losses… Show more

This paper is focused on the problem of Information Reconciliation (IR) for continuous variable Quantum Key Distribution (QKD). The main problem is quantization and assignment of labels to the samples of the Gaussian variables observed at Alice and Bob. Trouble is that most of the samples, assuming that the Gaussian variable is zero mean which is de-facto the case, tend to have small magnitudes and are easily disturbed by noise. Transmission over longer and longer distances increases the losses corresponding to a lower effective Signal-to-Noise Ratio (SNR) exasperating the problem. Quantization over higher dimensions is advantageous since it allows for fractional bit per sample accuracy which may be needed at very low SNR conditions whereby the achievable secret key rate is significantly less than one bit per sample. In this paper, we propose to use Permutation Modulation (PM) for quantization of Gaussian vectors potentially containing thousands of samples. PM is applied to the magnitudes of the Gaussian samples and we explore the dependence of the sign error probability on the magnitude of the samples. At very low SNR, we may transmit the entire label of the PM code from Bob to Alice in Reverse Reconciliation (RR) over public channel. The side information extracted from this label can then be used by Alice to characterize the sign error probability of her individual samples. Forward Error Correction (FEC) coding can be used by Bob on each subset of samples with similar sign error probability to aid Alice in error correction. This can be done for different subsets of samples with similar sign error probabilities leading to an Unequal Error Protection (UEP) coding paradigm. Show less

Coding over higher dimensions is always advantageous in Information Reconciliation for CV-QKD schemes, and given a d-dimensional vector X of Gaussian samples at Alice and the corresponding vector Y of quantized samples at Bob, the Slepian-Wolf theorem provides a bound on the achievability region of rate for the correlated sources. While simple in principle, the main problem here is how do you quantize a d-dimensional Gaussian vector when d can potentially be very large? To solve this problem… Show more

Coding over higher dimensions is always advantageous in Information Reconciliation for CV-QKD schemes, and given a d-dimensional vector X of Gaussian samples at Alice and the corresponding vector Y of quantized samples at Bob, the Slepian-Wolf theorem provides a bound on the achievability region of rate for the correlated sources. While simple in principle, the main problem here is how do you quantize a d-dimensional Gaussian vector when d can potentially be very large? To solve this problem, this paper presents the use of Permutation Modulation techniques to perform the quantization of the Gaussian vector X where d can be as high as several thousands. Show less

General types of Hybrid Electric Vehicle architectures along with different control strategies are described in this paper. The Series, Parallel and Parallel Through The Road architectures are investigated as the general concepts for HEVs and the advantages and disadvantages of these architectures with respect to cost and control complexity are also compared. Although there are different approaches to control HEVs in order to achieve higher fuel efficiency and lower emissions, but the different… Show more

General types of Hybrid Electric Vehicle architectures along with different control strategies are described in this paper. The Series, Parallel and Parallel Through The Road architectures are investigated as the general concepts for HEVs and the advantages and disadvantages of these architectures with respect to cost and control complexity are also compared. Although there are different approaches to control HEVs in order to achieve higher fuel efficiency and lower emissions, but the different control strategies have basic logics in common. In this regard, the general idea of controlling the HEVs for different topology is discussed and the performance, fuel consumption and emissions of the different HEV architecture is contrasted. Show less

Plug-in hybrid electric vehicles (PHEVs) represent an energy efficient alternative to conventional and hybrid electric vehicle counterparts which are not capable of drawing energy from the grid. Although the cost-saving and good environmental impacts are the benefits which make PHEVs popular but these advantages are significantly influenced by the high cost and limited lifetime of battery. Frequent charging and discharging cycles result in energy and power degradation which adversely affects… Show more

Plug-in hybrid electric vehicles (PHEVs) represent an energy efficient alternative to conventional and hybrid electric vehicle counterparts which are not capable of drawing energy from the grid. Although the cost-saving and good environmental impacts are the benefits which make PHEVs popular but these advantages are significantly influenced by the high cost and limited lifetime of battery. Frequent charging and discharging cycles result in energy and power degradation which adversely affects not only the life time of battery but also the performance and efficiency of the vehicle. A real-time power management system can be applied on-board to simultaneously optimize efficiency, battery cycling and other necessary cost functions. For this purpose, Model Predictive Control (MPC) as one of the dominant real-time control algorithms in Electrified Vehicle is used in this work. An EMS (Energy Management System) with Model Predictive Control-based (MPC) algorithm of a specific case of heavy-duty PHEV which draws their energy from the grid via catenary as well as the on-board battery will be described in this study and a simulation model for EMS of a CHEV (Catenary Hybrid Electric Vehicle) in which the cost of purchased electricity from the grid, the overall powertrain efficiency, and the number of battery full charge and discharge cycles are optimized simultaneously in real-time. Testing the algorithm in hardware in the loop fashion will also be planned. Show less

As part of EcoCAR 3 competition, the California State University, Los Angeles team is designing a Parallel Post Transmission Plug-in Hybrid Electric Vehicle based on a 2016 V6 Chevrolet Camaro. The redesigned vehicle shall maintain or exceed consumer acceptability in performance, utility and safety while reducing Well-to-Wheel Green House Gas emissions. Two control strategies in which the vehicle would operate are being developed: main and modified hybrid control algorithms. The modified… Show more

As part of EcoCAR 3 competition, the California State University, Los Angeles team is designing a Parallel Post Transmission Plug-in Hybrid Electric Vehicle based on a 2016 V6 Chevrolet Camaro. The redesigned vehicle shall maintain or exceed consumer acceptability in performance, utility and safety while reducing Well-to-Wheel Green House Gas emissions. Two control strategies in which the vehicle would operate are being developed: main and modified hybrid control algorithms. The modified control strategy introduces the optimized operating strategy in which the lower emissions and longer engine and battery life are achieved.
The vehicle model was developed using Autonomie software and the simulation results with the main and new modified control strategy are also presented. The optimization of the vehicle propulsion control strategy resulted in an increase of Charge Depletion range from 57.39 to 62.3 km as well as an increase in mpgge by 3.04% while reducing the effects of WTW GHG and WTW PEU by 0.29% and 7.38% respectively. In addition, the modified control algorithm would result in longer battery life by reducing the number of charge and discharge cycles, defining the higher Depth of Discharge (DOD) and avoiding deep discharging of the battery. Moreover, the longer engine life would be achieved by using the warm-up strategy to overcome the effect of engine cold start. Show less

As part of EcoCAR 3 competition, the California State University, Los Angeles team is designing a Parallel Post Transmission Plug-in Hybrid Electric Vehicle based on a 2016 V6 Chevrolet Camaro. The redesigned vehicle shall maintain or exceed consumer acceptability in performance, utility and safety while reducing Well-to-Wheel Green House Gas emissions. Two control strategies in which the vehicle would operate are being developed: main and modified hybrid control algorithms. The modified… Show more

As part of EcoCAR 3 competition, the California State University, Los Angeles team is designing a Parallel Post Transmission Plug-in Hybrid Electric Vehicle based on a 2016 V6 Chevrolet Camaro. The redesigned vehicle shall maintain or exceed consumer acceptability in performance, utility and safety while reducing Well-to-Wheel Green House Gas emissions. Two control strategies in which the vehicle would operate are being developed: main and modified hybrid control algorithms. The modified control strategy introduces the optimized operating strategy in which the lower emissions and longer engine and battery life are achieved.
The vehicle model was developed using Autonomie software and the simulation results with the main and new modified control strategy are also presented. The optimization of the vehicle propulsion control strategy resulted in an increase of Charge Depletion range from 57.39 to 62.3 km as well as an increase in mpgge by 3.04% while reducing the effects of WTW GHG and WTW PEU by 0.29% and 7.38% respectively. In addition, the modified control algorithm would result in longer battery life by reducing the number of charge and discharge cycles, defining the higher Depth of Discharge (DOD) and avoiding deep discharging of the battery. Moreover, the longer engine life would be achieved by using the warm-up strategy to overcome the effect of engine cold start. Show less

The optimization and integration process of Parallel-Through-the-Road Hybrid Electric Vehicle to perform the more efficient control system by upgrading the control codes and algorithm which provides more reliable control system.