JournalTOCs

International Journal of Vehicular Technology

Open Access journal
ISSN (Print) 1687-5702 - ISSN (Online) 1687-5710
Published by Hindawi Publishing Corporation

[267 journals]

Multiple-Observation-Based Robust Channel and Doppler Estimation in High Mobility Applications
- Abstract: Channel estimation is a challenging task, especially in high mobility applications due to the rapid variation of the propagation environment. This paper presents a new technique that exploits past channel impulse responses (CIRs) in order to trace and compensate Doppler frequency in mobile applications, enabling robust estimation of time-varying channel. Based on the fact that channel taps at different time instants can be fitted with a sinusoidal wave, a joint estimator is proposed to estimate the channel parameters. Therefore, the efficiency of the channel estimation can be improved and stringent delay requirements for the communication systems can also be satisfied. Simulation results show that system performance in terms of bit error rate (BER) is significantly improved with the proposed algorithm.
  PubDate: Mon, 13 May 2013 18:16:38 +000
ICT Innovations in Future Smart Cars
- PubDate: Mon, 13 May 2013 16:09:00 +000
Performance Evaluation of IEEE 1609 WAVE for Vehicular Communications
- Abstract: In IEEE 1609, it uses IEEE 802.11 Enhanced Distributed Channel Access (EDCA) mechanism to access the channel. IEEE 802.11 EDCA is a new wireless technology for wireless access in the vehicular environment (WAVE). It defines a new supplement to the existing IEEE 802.11 MAC protocol. In IEEE 802.11 EDCA, the aim is providing a QoS support. While the system serves different access categories (ACs), EDCA does not perform well under high load conditions. In order to improve the efficiency, we pay attention to the EDCA with transmit opportunity (TXOP) mechanism. We first proposed a Markov chain model and studied the behavior. We extend the model to support IEEE 802.11 EDCA and presented a more accurate analysis under nonideal channel environment. We also compared it with that without TXOP mechanism under channel error environment.
  PubDate: Tue, 07 May 2013 10:37:48 +000
Vehicle Yaw Rate Estimation Using a Virtual Sensor
- Abstract: Road vehicle yaw stability control systems like electronic stability program (ESP) are important active safety systems used for maintaining lateral stability of the vehicle. Vehicle yaw rate is the key parameter that needs to be known by a yaw stability control system. In this paper, yaw rate is estimated using a virtual sensor which contains kinematic relations and a velocity-scheduled Kalman filter. Kinematic estimation is carried out using wheel speeds, dynamic tire radius, and front wheel steering angle. In addition, a velocity-scheduled Kalman filter utilizing the linearized single-track model of the road vehicle is used in the dynamic estimation part of the virtual sensor. The designed virtual sensor is successfully tested offline using a validated, high degrees of freedom, and high fidelity vehicle model and using hardware-in-the-loop simulations. Moreover, actual road testing is carried out and the estimated yaw rate from the virtual sensor is compared with the actual yaw rate obtained from the commercial yaw rate sensor to demonstrate the effectiveness of the virtual yaw rate sensor in practical use.
  PubDate: Wed, 24 Apr 2013 14:43:45 +000
Human’s Overtrust in and Overreliance on Advanced Driver Assistance Systems: A Theoretical Framework
- Abstract: This paper gives a theoretical framework to describe, analyze, and evaluate the driver’s overtrust in and overreliance on ADAS. Although “overtrust” and “overreliance” are often used as if they are synonyms, this paper differentiates the two notions rigorously. To this end, two aspects, (1) situation diagnostic aspect and (2) action selection aspect, are introduced. The first aspect is to describe overtrust, and it has three axes: (1-1) dimension of trust, (1-2) target object, and (1-3) chances of observation. The second aspect, (2), is to describe overreliance on the ADAS, and it has other three axes: (2-1) type of action selected, (2-2) benefits expected, and (2-3) time allowance for human intervention.
  PubDate: Tue, 16 Apr 2013 11:23:00 +000
Modeling and Analysis of Connected Traffic Intersections Based on Modified Binary Petri Nets
- Abstract: We propose an approach for the modeling and analysis of two connected traffic intersections based on Petri nets (PNs). We first use a PN to model an isolated four-way signalized intersection; then we extend it to model two successive signalized intersections. We find that this model has unbounded places, which in turn results in some confliction problems. Hence, we introduce the concept of modified binary petri nets (MBPNs) to overcome the limitation and resolve the confliction problem when we design our model and its controller. This MBPN model is a powerful tool and can be useful for the modeling and analysis of many other traffic applications.
Predicting Driver Behavior Using Field Experiment Data and Driving Simulator Experiment Data: Assessing Impact of Elimination of Stop Regulation at Railway Crossings
- Abstract: We investigated the impact of deregulating the presence of stop signs at railway crossings on car driver behavior. We estimated the probability that a driver would stop inside the crossing, thereby obstructing the tracks, when a lead vehicle suddenly stopped after the crossing and a stop regulation was eliminated. We proposed a new assessment method of the driving behavior as follows: first, collecting driving behavior data in a driving simulator and in a real road environment; then, predicting the probability based on the collected data. In the simulator experiment, we measured the distances between a lead vehicle and the driver’s vehicle and the driver’s response time to the deceleration of the leading vehicle when entering the railway crossing. We investigated the influence of the presence of two leading vehicles on the driver’s vehicle movements. The deceleration data were recorded in the field experiments. Slower driving speed led to a higher probability of stopping inside the railway crossing. The probability was higher when the vehicle in front of the leading vehicle did not slow down than when both the lead vehicle and the vehicle in front of it slowed down. Finally, advantages of our new assessment method were discussed.
Palm Personal Identification for Vehicular Security with a Mobile Device
- Abstract: Security certification is drawing more and more attention in recent years; the biometric technology is used in a variety of different areas of security certification. In this paper, we propose a palm image recognition method to identify an individual for vehicular application; it uses palm image as a key for detecting the car owner. We used mobile phone cameras to take palm images and performed a new identification approach by using feature regularization of palm contour. After identification is confirmed, the phone uses Bluetooth/WiFi to connect the car to unlock it. In our evaluation, the experiments show that our approach is effective and feasible.
Vehicle Dynamics Approach to Driver Warning
- Abstract: This paper discusses a concept for enhanced active safety by introducing a driver warning system based on vehicle dynamics that predicts a potential loss of control condition prior to stability control activation. This real-time warning algorithm builds on available technologies such as the Electronic Stability Control (ESC). The driver warning system computes several indices based on yaw rate, side-slip velocity, and vehicle understeer using ESC sensor suite. An arbitrator block arbitrates between the different indices and determines the status index of the driving vehicle. The status index is compared to predetermined stability levels which correspond to high and low stability levels. If the index exceeds the high stability level, a warning signal (haptic, acoustic, or visual) is issued to alert the driver of a potential loss of control and ESC activation. This alert will remain in effect until the index is less than the low stability level at which time the warning signal will be terminated. A vehicle speed advisory algorithm is integrated with the warning algorithm to provide a desired vehicle speed of a vehicle traveling on a curve. Simulation results and vehicle tests were conducted to illustrate the effectiveness of the warning algorithm.
Evaluation of a Navigation Radio Using the Think-Aloud Method
- Abstract: In this experiment, 13 licensed drivers performed 20 tasks with a prototype navigation radio. Subjects completed such tasks as entering a street address, selecting a preset radio station, and tuning to an XM station while “thinking aloud” to identify problems with operating the prototype interface. Overall, subjects identified 64 unique problems with the interface; 17 specific problems were encountered by more than half of the subjects. Problems are related to inconsistent music interfaces, limitations to destination entry methods, icons that were not understood, the lack of functional grouping, and similar looking buttons and displays, among others. An important project focus was getting the findings to the developers quickly. Having a scribe to code interactions in real time helped as well as directed observations of test sessions by representatives of the developers. Other researchers are encouraged to use this method to examine automotive interfaces as a complement to traditional usability testing.
A Comparative Analysis of Subjective Quality of the Mobility between a New Portable Electric Transportation Mode and Walking
- Abstract: To analyze the psychological impacts of the introduction of new portable electric transportation modes, we implemented an experiment using a personal mobile vehicle (PMV). We investigated its effects on 2 types of the subjective quality of mobility (SQM): instrumental aspects including “easiness” and “speed”: and affective aspects including “enjoyment,” “seeing scenery,” and “enjoying the atmosphere.” The result indicated that PMV might contribute to the improvement of the instrumental aspects of SQM, but walking was regarded as more preferable in terms of the affective aspects. The results suggest that such a new transportation mode could contribute to the improvement of subjective quality of mobility, if and only if it can be introduced in an appropriate situation.
Efficient Noninteractive Secure Protocol Enforcing Privacy in Vehicle-to-Roadside Communication Networks
- Abstract: Vehicular ad hoc networks (VANETs) have attracted extensive attentions in recent years for their promises in improving safety and enabling other value-added services. In this paper, we propose an efficient noninteractive secure protocol preserving the privacy of drivers in vehicle-to-roadside (V2R) communication networks with the ability of tracing malicious drivers only by a third trusted party (TTP), who is assumed to be fully trusted. Our proposed protocol can provide these complex requirements depending on symmetric cryptographic algorithms. The drivers can change the symmetric key used for message encryption with each message transmission and find noninteractively new values to be correctly used for verification and tracing in case of malicious behavior. The advantages of symmetric cryptographic algorithms over asymmetric algorithms are the faster processing speed and the shorter message length which makes it suitable for real-time applications such as V2R communications. An efficient key revocation scheme will be also described.
A Neurofuzzy Approach to Modeling Longitudinal Driving Behavior and Driving Task Complexity
- Abstract: Technological innovations can be assumed to have made the driving task more complex. It is, however, not yet clear to what extent this complexity leads to changes in longitudinal driving behavior. Furthermore, it remains to be seen how these adaptation effects can best be modeled mathematically. In order to determine the effect of complexity on empirical longitudinal driving behavior we performed a driving simulator experiment with a repeated measures design. Through this experiment we established that complexity of the driving task leads to substantial changes in speed and spacing. In order to provide insight into how complexity is actually related to changes in longitudinal driving behavior we introduce a new theoretical framework based on the Task-Capability-Interface model. Finally in this paper we take some first steps towards modeling of adaptation effects in longitudinal driving behavior in relation to complexity of the driving task through the introduction of a new neurofuzzy car-following model and based on the proposed theoretical framework. In this paper we show that this model yields a relatively good prediction of longitudinal driving behavior in case of driving conditions with differing complexity. The paper finishes with a discussion section and recommendations for future research.
A Geo-Aware and VRP-Based Public Bicycle Redistribution System
- Abstract: Public Bicycle System (PBS) has been developed for short-distance transportation as a part of the mass transportation system. The supply and demand of bikes in PBS is usually unbalanced at different stations and needs to be continuously and widely monitored and redistributed. The bicycle redistribution is a part of the vehicle routing problem (VRP). We can apply solutions to the VRP to redistribute bicycle efficiently. However, most solutions to the VRP use the Euclidean distance as the condition factor, which does not take road conditions, traffic regulations, and geographical factors into account, resulting in unnecessary waste of delivery time and human resources. In this work, we propose an actual path distance optimization method for the VRP to adapt the several additional constraints of road problems. We also implement a system that integrates real-time station information, Web GIS, the urban road network, and heuristics algorithms for PBS. The system includes a simulator inside that can assist PBS managers to do the route planning efficiently and find the best scheduling strategy to achieve hotspot analysis and the adjustment of station deployment strategies to reduce PBS operation cost.
Development and Evaluation of Automotive Speech Interfaces: Useful Information from the Human Factors and the Related Literature
- Abstract: Drivers often use infotainment systems in motor vehicles, such as systems for navigation, music, and phones. However, operating visual-manual interfaces for these systems can distract drivers. Speech interfaces may be less distracting. To help designing easy-to-use speech interfaces, this paper identifies key speech interfaces (e.g., CHAT, Linguatronic, SYNC, Siri, and Google Voice), their features, and what was learned from evaluating them and other systems. Also included is information on key technical standards (e.g., ISO 9921, ITU P.800) and relevant design guidelines. This paper also describes relevant design and evaluation methods (e.g., Wizard of Oz) and how to make driving studies replicable (e.g., by referencing SAE J2944). Throughout the paper, there is discussion of linguistic terms (e.g., turn-taking) and principles (e.g., Grice’s Conversational Maxims) that provide a basis for describing user-device interactions and errors in evaluations.
A Driver Face Monitoring System for Fatigue and Distraction Detection
- Abstract: Driver face monitoring system is a real-time system that can detect driver fatigue and distraction using machine vision approaches. In this paper, a new approach is introduced for driver hypovigilance (fatigue and distraction) detection based on the symptoms related to face and eye regions. In this method, face template matching and horizontal projection of top-half segment of face image are used to extract hypovigilance symptoms from face and eye, respectively. Head rotation is a symptom to detect distraction that is extracted from face region. The extracted symptoms from eye region are (1) percentage of eye closure, (2) eyelid distance changes with respect to the normal eyelid distance, and (3) eye closure rate. The first and second symptoms related to eye region are used for fatigue detection; the last one is used for distraction detection. In the proposed system, a fuzzy expert system combines the symptoms to estimate level of driver hypo-vigilance. There are three main contributions in the introduced method: (1) simple and efficient head rotation detection based on face template matching, (2) adaptive symptom extraction from eye region without explicit eye detection, and (3) normalizing and personalizing the extracted symptoms using a short training phase. These three contributions lead to develop an adaptive driver eye/face monitoring. Experiments show that the proposed system is relatively efficient for estimating the driver fatigue and distraction.
Detection of Overhead Contact Lines with a 2D-Digital-Beamforming Radar System for Automatic Guidance of Trolley Trucks
- Abstract: The benefit of trolley truck systems is the substitution of the diesel fuel by the cheaper and more ecological electrical energy. Trolley trucks are powered by electricity from two overhead contact lines, where one is the supply and the other the return conductor. Such trolley trucks are used for haulage at open pit mining sites but could also be used for freight traffic at roadways in the future. Automatic guidance prevents the trolley-powered trucks from leaving the track and thus allows higher operating speeds, higher loading capacity, and greater efficiency. Radar is the ideal sensing technique for automatic guidance in such environments. The presented radar system with two-dimensional digital beamforming capability offers a compact measurement solution as it can be installed on top of the truck. Besides the distance measurement, this radar system allows to detect the location and inclination of the overhead contact lines by digital beamforming in two dimensions. Besides automatic guidance, the knowledge of the inclination of the overhead contact lines could allow automatic speed adaption, which would help to achieve maximum speed especially in hilly terrain.
A Comprehensive Evaluation of RPL under Mobility
- Abstract: This paper focuses on routing for vehicles getting access to infrastructure either directly or via multiple hops through other vehicles. We study routing protocol for low-power and lossy networks (RPL), a tree-based routing protocol designed for sensor networks. Many design elements from RPL are transferable to the vehicular environment. We provide a simulation performance study of RPL and RPL tuning in VANETs. More specifically, we seek to study the impact of RPL's various parameters and external factors (e.g., various timers and speeds) on its performance and obtain insights on RPL tuning for its use in VANETs. We then fine tune RPL and obtain performance gain over existing RPL.
Modeling and Deployment of Model-Based Decentralized Embedded Diagnosis inside Vehicles: Application to Smart Distance Keeping Function
- Abstract: The deployment of a fault diagnosis strategy in the Smart Distance Keeping (SDK) system with a decentralized architecture is presented. The SDK system is an advanced Adaptive Cruise Control (ACC) system implemented in a Renault-Volvo Trucks vehicle to increase safety by overcoming some ACC limitations. One of the main differences between this new system and the classical ACC is the choice of the safe distance. This latter is the distance between the vehicle equipped with the ACC or the SDK system and the obstacle-in-front (which may be another vehicle). It is supposed fixed in the case of the ACC, while variable in the case of the SDK. The variation of this distance depends essentially on the relative velocity between the vehicle and the obstacle-in-front. The main goal of this work is to analyze measurements, issued from the SDK elements, in order to detect, to localize, and to identify some faults that may occur. Our main contribution is the proposition of a decentralized approach permitting to carry out an on-line diagnosis without computing the global model and to achieve most of the work locally avoiding huge extra diagnostic information traffic between components. After a detailed description of the SDK system, this paper explains the model-based decentralized solution and its application to the embedded diagnosis of the SDK system inside Renault-Volvo Truck with five control units connected via a CAN-bus using “Hardware in the Loop” (HIL) technique. We also discuss the constraints that must be fulfilled.
A Real-Time Embedded Blind Spot Safety Assistance System
- Abstract: This paper presents an effective vehicle and motorcycle detection system in the blind spot area in the daytime and nighttime scenes. The proposed method identifies vehicle and motorcycle by detecting the shadow and the edge features in the daytime, and the vehicle and motorcycle could be detected through locating the headlights at nighttime. First, shadow segmentation is performed to briefly locate the position of the vehicle. Then, the vertical and horizontal edges are utilized to verify the existence of the vehicle. After that, tracking procedure is operated to track the same vehicle in the consecutive frames. Finally, the driving behavior is judged by the trajectory. Second, the lamps in the nighttime are extracted based on automatic histogram thresholding, and are verified by spatial and temporal features to against the reflection of the pavement. The proposed real-time vision-based Blind Spot Safety-Assistance System has implemented and evaluated on a TI DM6437 platform to perform the vehicle detection on real highway, expressways, and urban roadways, and works well on sunny, cloudy, and rainy conditions in daytime and night time. Experimental results demonstrate that the proposed vehicle detection approach is effective and feasible in various environments.
Context-Aware Multicast Protocol for Emergency Message Dissemination in Vehicular Networks
- Abstract: Road traffic accidents can be reduced by providing early warning to drivers through wireless ad hoc networks. When a vehicle detects an event that may lead to an imminent accident, the vehicle disseminates emergency messages to alert other vehicles that may be endangered by the accident. In many existing broadcast-based dissemination schemes, emergency messages may be sent to a large number of vehicles in the area and can be propagated to only one direction. This paper presents a more efficient context-aware multicast protocol that disseminates messages only to endangered vehicles that may be affected by the emergency event. The endangered vehicles can be identified by calculating the interaction among vehicles based on their motion properties. To ensure fast delivery, the dissemination follows a routing path obtained by computing a minimum delay tree. The multicast protocol uses a generalized approach that can support any arbitrary road topology. The performance of the multicast protocol is compared with existing broadcast protocols by simulating chain collision accidents on a typical highway. Simulation results show that the multicast protocol outperforms the other protocols in terms of reliability, efficiency, and latency.
River Flow Lane Detection and Kalman Filtering-Based B-Spline Lane Tracking
- Abstract: A novel lane detection technique using adaptive line segment and river flow method is proposed in this paper to estimate driving lane edges. A Kalman filtering-based B-spline tracking model is also presented to quickly predict lane boundaries in consecutive frames. Firstly, sky region and road shadows are removed by applying a regional dividing method and road region analysis, respectively. Next, the change of lane orientation is monitored in order to define an adaptive line segment separating the region into near and far fields. In the near field, a 1D Hough transform is used to approximate a pair of lane boundaries. Subsequently, river flow method is applied to obtain lane curvature in the far field. Once the lane boundaries are detected, a B-spline mathematical model is updated using a Kalman filter to continuously track the road edges. Simulation results show that the proposed lane detection and tracking method has good performance with low complexity.
Intelligent Lane Reservation System for Highway(s)
- Abstract: Highways tend to get congested because of the increase in the number of cars travelling on them. There are two solutions to this. The first one, which is also expensive, consists in building new highways to support the traffic. A much cheaper alternative consists in the introduction of advanced intelligent traffic control systems to manage traffic and increase the efficiency of the already existing highways. Intelligent lane reservation system for highways (ILRSH) is such a software control system. It is designed to assist and automate the use of a highway lane as a reserved lane. The idea is to allow and support drivers to travel at a speed higher, if in return they are willing to pay a small fee to reserve an empty virtual slot on the reserved lane. This slot is valid for a portion and of the highway and a time window, so each driver pays the fee depending thier its travelling needs. In return, drivers are guaranteed a congestion-free travel on that portion. In this paper, we present the proposed architecture of the ILRSH and its subsystems. The system is based on several proposed algorithms designed to assist the drivers, enter or exit the reserved lane, based on real-world driving observations. We present extensive simulation results showing the feasibility of the proposed approach, that can easily be implemented with little costs on already-existing highways, and the increase in traffic efficiency.
DSP-Based Sensor Fault Detection and Post Fault-Tolerant Control of an Induction Motor-Based Electric Vehicle
- Abstract: This paper deals with sensor fault detection within a reconfigurable direct torque control of an induction motor-based electric vehicle. The proposed strategy concerns current, voltage, and speed sensors faults that are detected and followed by post fault-tolerant control to allow the vehicle continuous operation. The proposed approach is validated through experiments on an induction motor drive and simulations on an electric vehicle using a European urban and extraurban driving cycle.
A Pedestrian Navigation System Using Cellular Phone Video-Conferencing Functions
- Abstract: A user’s position-specific field has been developed using the Global Positioning System (GPS) technology. To determine the position using cellular phones, a device was developed, in which a pedestrian navigation unit carries the GPS. However, GPS cannot specify a position in a subterranean environment or indoors, which is beyond the reach of transmitted signals. In addition, the position-specification precision of GPS, that is, its resolution, is on the order of several meters, which is deemed insufficient for pedestrians. In this study, we proposed and evaluated a technique for locating a user’s 3D position by setting up a marker in the navigation space detected in the image of a cellular phone. By experiment, we verified the effectiveness and accuracy of the proposed method. Additionally, we improved the positional precision because we measured the position distance using numerous markers.
StopWatcher: A Mobile Application to Improve Stop Sign Awareness for Driving Safety
- Abstract: Stop signs are the primary form of traffic control in the United States. However, they have a tendency to be much less effective than other forms of traffic control like traffic lights. This is due to their smaller size, lack of lighting, and the fact that they may become visually obscured from the road. In this paper, we offer a solution to this problem in the form of a mobile application implemented in the Android platform: StopWatcher. It is designed to alert a driver when they are approaching a stop sign using a voice notification system (VNS). A field test was performed in a snowy environment. The test results demonstrate that the application can detect all of the stop signs correctly, even when some of them were obstructed by the snow, which in turn greatly improves the user awareness of stop signs.
A New Movement Recognition Technique for Flight Mode Detection
- Abstract: Nowadays, in the aeronautical environments, the use of mobile communication and other wireless technologies is restricted. More specifically, the Federal Communications Commission (FCC) and the Federal Aviation Administration (FAA) prohibit the use of cellular phones and other wireless devices on airborne aircraft because of potential interference with wireless networks on the ground, and with the aircraft's navigation and communication systems. Within this context, we propose in this paper a movement recognition algorithm that will switch off a module including a GSM (Global System for Mobile Communications) device or any other mobile cellular technology as soon as it senses movement and thereby will prevent any forbidden transmissions that could occur in a moving airplane. The algorithm is based solely on measurements of a low-cost accelerometer and is easy to implement with a high degree of reliability.
Lidar Data Analysis for Time to Headway Determination in the DriveSafe Project Field Tests
- Abstract: The DriveSafe project was carried out by a consortium of university research centers and automotive OEMs in Turkey to reduce accidents caused by driver behavior. A huge amount of driving data was collected from 108 drivers who drove the instrumented DriveSafe vehicle in the same route of 25 km of urban and highway traffic in Istanbul. One of the sensors used in the DriveSafe vehicle was a forward-looking LIDAR. The data from the LIDAR is used here to determine and record the headway time characteristics of different drivers. This paper concentrates on the analysis of LIDAR data from the DriveSafe vehicle. A simple algorithm that only looks at the forward direction along a straight line is used first. Headway times based on this simple approach are presented for an example driver. A more accurate detection and tracking algorithm taken from the literature are presented later in the paper. Grid-based and point distance-based methods are presented first. Then, a detection and tracking algorithm based on the Kalman filter is presented. The results are demonstrated using experimental data.
Optimisation of the Nonlinear Suspension Characteristics of a Light Commercial Vehicle
- Abstract: The optimum functional characteristics of suspension components, namely, linear/nonlinear spring and nonlinear damper characteristic functions are determined using simple lumped parameter models. A quarter car model is used to represent the front independent suspension, and a half car model is used to represent the rear solid axle suspension of a light commercial vehicle. The functional shapes of the suspension characteristics used in the optimisation process are based on typical shapes supplied by a car manufacturer. The complexity of a nonlinear function optimisation problem is reduced by scaling it up or down from the aforementioned shape in the optimisation process. The nonlinear optimised suspension characteristics are first obtained using lower complexity lumped parameter models. Then, the performance of the optimised suspension units are verified using the higher fidelity and more realistic Carmaker model. An interactive software module is developed to ease the nonlinear suspension optimisation process using the Matlab Graphical User Interface tool.
A 7-Level Single DC Source Cascaded H-Bridge Multilevel Inverter with a Modified DTC Scheme for Induction Motor-Based Electric Vehicle Propulsion
- Abstract: This paper presents a new hybrid cascaded H-bridge multilevel inverter motor drive DTC scheme for electric vehicles where each phase of the inverter can be implemented using a single DC source. Traditionally, each phase of the inverter requires DC source for output voltage levels. In this paper, a scheme is proposed that allows the use of a single DC source as the first DC source which would be available from batteries or fuel cells, with the remaining () DC sources being capacitors. This scheme can simultaneously maintain the capacitors of DC voltage level and produce a nearly sinusoidal output voltage due to its high number of output levels. In this context, high performances and efficient torque and flux control are obtained, enabling a DTC solution for hybrid multilevel inverter powered induction motor drives intended for electric vehicle propulsion. Simulations and experiments show that the proposed multilevel inverter and control scheme are effective and very attractive for embedded systems such as automotive applications.