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Table of Contents
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Imaging and Image Analysis 3 (Regular Session) 15:30-15:52 MoDT2.1 An Evolutionary Optimized Vehicle Tracker in Collaboration with a Detection System, pp. 208-213. Haselhoff, Anselm Univ. of Wuppertal Kummert, Anton Univ. of Wuppertal 15:52-16:14 MoDT2.2 Real-Time Highway Traffic Information Extraction Based on Airborne Video, pp. 214-219. Li, Qingquan Wuhan Univ. Lei, Bo Wuhan Univ. Yu, Yang Wuhan Univ. Hou, Rui South-Central Univ. for Nationalities 16:14-16:36 MoDT2.3 A Hardware Implementation of Pyramidal KLT Feature Tracker for Driving Assistance Systems, pp. 220-225. Jang, Wonjun Sogang Univ. Oh, Sungchan Sogang Univ. Kim, Gyeonghwan Sogang Univ. 16:36-16:58 MoDT2.4 An Experiment of a 3D Real-Time Robust Visual Odometry for Intelligent Vehicles, pp. 226-231. Rodriguez Florez, Sergio Alberto Heudiasyc Lab. Univ. de Tech. de Compičgne Fremont, Vincent Univ. de Tech. de Compičgne Bonnifait, Philippe Univ. de Tech. de Compičgne MoDT3 ITS Operational Strategies and the Environment (Plenary Session)
Grand A
15:30-15:52 MoDT3.1 Environmentally-Beneficial Intelligent Transportation Systems (I)*. Barth, Matthew Univ. of California-Riverside 15:52-16:14 MoDT3.2 The Potential Role That Transportation Systems Management and Operations Can Play in Reducing Greenhouse Gas Emissions (I)*. Neudorff, Louis Iteris, Inc. 16:14-16:36 MoDT3.3 ITS, Enabler for a Sustainable Environment -- a California PATH Program Perspective (I)*. Zhang, Wei-Bin Univ. of California at Berkeley MoDT4 Travel Behavior under ITS (Regular Session)
Grand C
15:30-15:52 MoDT4.1 Analysis of Congestion Points Based on Probe Car Data, pp. 232-236. Li, Man Hitachi (China) Res. & Development Corp. Zhang, Yuhe Hitachi (China) Res. & Development Corp. Wang, Wenjia Hitachi (China) Res. & Development Corp. 15:52-16:14 MoDT4.2 Advanced Framework for Illumination Invariant Traffic Density Estimation, pp. 237-242. Janney, Pranam Univ. of New South Wales Geers, Donald Glenn NICTA 16:14-16:36 MoDT4.3 Vehicle Behavior Understanding Based on Movement String, pp. 243-248. Hao, JiuYue BeiHang Univ. Sheng, Hao BeiHang Univ. Li, Chao BeiHang Univ. Xiong, Zhang BeiHang Univ. Hussain, Ejaz BeiHang Univ. 16:36-16:58 MoDT4.4 Improved Multi-Level Pedestrian Behavior Prediction Based on Matching with Classified Motion Patterns, pp. 249-254. Chen, Zhuo Univ. of Hong Kong Yung, Nelson H. C. Univ. of Hong Kong TuAT1 Topics in ITS 1 (Regular Session)
Regency A
08:30-08:52 TuAT1.1 Multi-Sensor Integration in the Vehicular System Using the IEEE1451 Std.: A Case Study, pp. 255-260. Cortés, Francisco Univ. of Seville Barrero, Federico Univ. of Seville Toral-Marín, Sergio Univ. of Seville Prieto, Joel Univ. of Seville Guevara, Jean Catholic Univ. of Asunción, Paraguay 08:52-09:14 TuAT1.2 Road Traffic Estimation with Signal Matching in Mobile Phone Using Large-Size Database, pp. 261-266. Promnoi, Sunisa King's Mongkut Univ. of Tech. Thonburi Tangamchit, Poj King's Mongkut Univ. of Tech. Thonburi Pattara-atikom, Wasan National Electronics and Computer Tech. Center 09:14-09:36 TuAT1.3 Short-Time OD Matrix Estimation for a Complex Junction Using Fuzzy-Timed High-Level Petri Nets, pp. 267-272. Biletska, Krystyna UMR CNRS 6599 Heudiasyc, Univ. de Tech. de Compičgne Masson, Marie-Hélčne UMR CNRS 6599 Heudiasyc and Univ. de Picardie Jules Verne
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2009 – submission 75 Proceedings of the 12th International IEEEITSC Conference on Intelligent Transportation Systems, St. Louis, MO, USA, October 3-7, 2009
1 TuAT1.1
Multi–sensor Integration in the Vehicular System using the IEEE1451 Std.: A Case Study F. Cortés, F. Barrero, Senior Member, IEEE, S. Toral, Senior Member, IEEE, J. Prieto, J. Guevara
Abstract—The integration of the electronic equipments into the vehicular system has become a necessity to enhance safety in road transportation. The Information and Communications Technologies (ICT) make this integration possible. The IEEE Std. 1451 standardizes the interface and communication protocol between networked electronic equipments. This paper proposes the architecture to integrate the existing electronic equipments into the vehicular system using the IEEE 1451 standard. The vehicle propulsion module is used as a case example. Index Terms—intelligent vehicles, smart transducers, heterogeneous sensor network, IEEE Std. 1451.
I. INTRODUCTION
T
he automotive industry is witnessing the explosion in the use of electronic systems. The average vehicle includes more than 50 electronics controllers. Integrate all of the electronics connected to the vehicle network, and ensure everything works properly is a difficult and expensive task. To avoid these problems, automobile vendors and parts manufacturers have developed In– Vehicle Networking (IVN) systems. Electronic components are connected to an Electronic Control Unit (ECU) through a shared network cable [1], and installed without changing the harness system. Consequently, the assembly process and the maintenance of the electronic systems are simpler. Several protocols have been developed to interconnect these electronic components, including the Controller Area Network (CAN), J1850, and Local Interconnect Network (LIN) protocols. In addition, X–by–wire protocols have being also developed to expand the application area of IVN systems to real–time components, such as time–triggered protocol/class C (TTP/C), time–triggered CAN (TTCAN), and FlexRay. These developments, and their use in intelligent vehicle systems enhancing safety for drivers and
The authors gratefully acknowledge the Spanish Government for the economical support provided within the National Research, Development and Innovation Plan, under references DPI2005/04438 and DPI2007/60128. F. Cortés, F. Barrero, S. Toral, and J. Prieto are with the Electronic Engineering Department, University of Seville, Spain (e–mail:
[email protected]). J. Guevara is with the Electronic Engineering Department, Catholic University of Asunción, Paraguay.
978-1-4244-5521-8/09/$26.00 ©2009 IEEE
passengers, have promoted the IVN systems till becoming a center of interest in the research field. Recently, the concept and design methodology of an international standard for smart transducers (IEEE Std. 1451) has been proposed for IVN systems [2]. The IEEE 1451 family of international standards provides an open platform for the development of networked electronic modules. The standard offers the ability to simplify the connectivity of transducers (sensors or actuators) to industrial networks, allowing sensor manufacturers to support multiple control networks. In particular, the “Plug and Play” of 1451–compliant transducers with different control networks at the device level is available. Consequently, the electronic modules are independent of the IVN protocol type using the standard, reducing manufacturer cost and the replacement module cost if an IVN system fails. The propulsion modules, based on electronic equipment with several components including several transducers and a microcontroller, are modern IVN systems. As a component of the intelligent vehicle, it can be used to assist the driver with safe driving. This paper describes the concept and design methodology of an IEEE–1451–based propulsion module for IVN system. The integration of an electric propulsion module in the vehicular system is used as a case example due to their excellent future perspectives. Previous IEEE–1451–based smart propulsion drives for Electrical Vehicles (EV) have been recently proposed based on different smart modules or sensors/actuators IEEE 1451 compliant [2]. The main problem of these proposals is the degradation of the drive performance due to the time delay caused by the IEEE 1451 architecture. This degradation should be limited or avoided in intelligent vehicles for safety reasons. In this paper, the development of a 1451 compliant smart transducer to accomplish the propulsion module of an EV is presented, to analyze its viability. The paper is organized as follows. First, a brief overview of the IEEE 1451 standard is given in section II. Then, section III analyzes advanced EV propulsion drives, used as a case example for the integration of electronic equipments into the IVN. Afterwards, the design and implementation of the IEEE–1451–compliant electric propulsion module is shown 255
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TII
Analog + Digital
Multidrop Bus Wireless Interface CAN Interface
The purpose of the IEEE 1451 Standards for Smart Transducer Interface is to define a set of common interfaces for connecting sensors and actuators to microprocessor–based systems, instruments, and field networks in a network–independent fashion [3]. The main goals of the standard are developing network–independent and vendor–independent transducer interfaces; allowing transducers to be replaced and/or moved with minimum effort; eliminating error prone and manual system configuration steps; supporting a general transducer data, control, timing, configuration and calibration model; and developing Transducer Electronic Data Sheets (TEDS) that remain with the transducer during normal operation. Consequently, the IEEE 1451 family of international standards provides an open platform for the development of networked electronic modules. The IEEE 1451 smart transducer architecture defines two major components: a Network Capable Application Processor (NCAP) and a Transducer Interface Module (TIM). The NCAP, a network node, performs application processing and network communication function, while the TIM consists of a transducer signal conditioning and data conversion system and a number of sensors and actuators, with a combination of up to 255 devices. Six separate standards are included in the IEEE 1451 family. IEEE1451.0 defines a common set of commands and communication protocol for accessing transducers in the TIM. The aim of IEEE 1451.0 is to encourage compatibility across the IEEE 1451 family. IEEE1451.1 defines a common object model for smart transducers along with interface specifications for the components of the model [4]. It defines the NCAP to interface transducers into networks. The NCAP accesses the TIMs using different physical interfaces. IEEE 1451.2 specifies a ten–wire point–to–point interface [5] called Transducer Independent Interface (TII). The IEEE 1451.2 defines a unique TIM named STIM or Smart Transducer Interface Module. IEEE 1451.3 establishes a distributed multidrop interface network sharing a common pair of wires. This standard specifies multiple TIMs named TBIM or Transducer Bus Interface Modules, and it is intended to allow synchronized reading of large sensor arrays on a parallel transducer bus using the multidrop connectivity by defining channel identification protocols, hot–swap protocols, time synchronization protocols, and the read and write logic functions used to access the TEDS and transducer data. IEEE 1451.4 presents a mixed–mode communication protocol for analog
RFID Interface
II. OVERVIEW OF THE IEEE1451 STD.
transducers with analog and digital operation [6], and it defines a mechanism for adding self–identification technology to traditional analog sensors and actuators. IEEE 1451.5 defines wireless communication methods. Finally, other well–known interfaces, the CANopen interface and the Radio Frequency Identification (RFID) interface, will meet the proposed IEEE P1451.6 and IEEE P1451.7 standards. The overall structure for the standard is shown in Fig. 1.
Network
in section IV, and the obtained results are presented in section V. Finally, the conclusions are presented.
2
Fig. 1. IEEE 1451 structure overview.
III. MODERN PROPULSION DRIVES IN EV The price of fossil fuels and the more strict regulation in environmental issues such as better energy efficiency or less pollution is promoting electric propulsion systems like Electrical Vehicles (EVs). EV is a road vehicle which involves with electric propulsion [7]. With this broad definition in mind, EVs may include Battery Electric Vehicles (BEVs), Hybrid Electric Vehicles (HEVs), and Fuel–Cell Electric Vehicles (FCEVs). EV is a multidisciplinary subject which covers broad and complex aspects like propulsion technology and energy source technology. An EV basically consists of a battery, an electronic converter, an electric motor, and a speed and/or torque sensor [8]. The propulsion has been traditionally obtained from conventional electric motors like 3–phase squirrel cage induction motors, Fig. 2. However, if one of the phases is lost, the rotatory field also disappears and the machine stops. Multi–phase drives offer the improvement of the system reliability, which is of great interest in modern EV applications [9]. Independently of the number of phases the multi–phase machine has, it only needs two degrees of freedom to generate a rotatory field, and if one phase is lost the drive continues operating although at different rating values. The low inverter DC link voltage provided by the battery imposes high–phase currents in the electric drive, and makes also multiphase drives especially suitable in the EV propulsion systems by means of current splitting [10]. Among different multiphase motor drive solutions, the 256
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most widely discussed in EV applications is the VSI fed dual 3–phase induction machine [11]–[15]. This induction machine has two sets of 3–phase windings which are spatially phase shifted by 30 electrical degrees with isolated neutrals, as shown in Fig. 3.
3
architecture.
Fig. 4. Block diagram of the proposed distributed control environment.
Fig. 2. EV scheme.
Fig. 3. Dual 3–phase induction motor drive.
Control of these propulsion drives has been studied during the last years. It is usually based on the multidimensional extension of the three–phase controllers, coping with unbalanced currents, machine asymmetries and large harmonic currents. Interesting developments have been recently reported in the literature in the application of vector control schemes, direct torque control techniques, and PWM control of multiphase voltage source inverters [9], [16], [17], [18]. The scheme proposed in [19]–[21], including speed and torque controllers, has been used in this study. IV. IEEE1451 COMPLIANT PROPULSION DRIVE The architecture of the proposed IEEE1451–based smart propulsion drive is shown in Fig. 4. The IEEE1451 compliant propulsion drive is based on the IEEE1451.2 Std., and two electronic equipments: the propulsion drive control system and a smart transducer module. The main problem caused by previous proposals [2], the time delay of the drive performance which degrades the safety response of an intelligent vehicle, is reduced using the presented
A smart transducer module (STIM) is designed to feature an IEEE1451.2 compliant interface. The STIM is electronically connected with the NCAP, using the TII interface, and with the control board, using a SPI interface (Serial Peripheral Interface). The standard connection between the STIM and the NCAP layers is the TII, a 10– wire bus designed for feeding the STIM and for exchanging information [22]. The characteristics of the proposed STIM are as follows: provide information for each sensor/actuator in the EV propulsion module, system integration using a self–identification technique, triggered I/O functions, and electronically connected with the NCAP and the electrical machine drive control board. The programmable features of the propulsion drive system must be stored in a non volatile memory using the TEDS Format, Table I. The TEDS is an electronically readable memory and a datasheet describing the transducer characteristic. It must automatically set up the environment, and it must be accessible from the STIM. The implemented TEDS consist of the META–TEDS and the CHANNEL–TEDS that are mandatory, although other TEDS can be also easily included. The META-TEDS provides the interfaces with all of the information needed to gain access to any channel, plus information common to all channel. The CHANNEL–TEDS supplies all of the information concerning the channel being addressed to enable the proper operation of the channel [22]. To define the CHANNEL–TEDS, a study of the EV propulsion system is necessary. The EV motor needs different parameters to its control. Most of these parameters are physically linked in the real system, although other ones are estimated from the real measurements. The motor drive is speed and torque controlled, and its accuracy depends on the currents, temperature and torque values. Consequently, a good knowledge of these critical parameters is necessary, and in our case, a maximum speed, current, torque and temperature limits have been considered. The 1451.2 Std. defines general and specific transducers channels. Figure 5 illustrates the proposed motor drive model which it is composed of 16 transducers channels, and Table II summarizes the implemented transducers, providing the necessary information to access the EV propulsion drive module. Each TEDS initializes its transducer with a default parameter value.
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TABLE I TEDS: TRANSDUCER ELECTRONIC DATA SHEETS TEDS Specification Contain the overall description of TEDS data META–TEDS structure, worst case STIM timing parameters and channel grouping information. Contains upper/lower range limits, physical units, Channel–TEDS warm up time, presence of self test, uncertainty, data model, calibration model, and triggering parameters.
Car computer Module
NCAP
Fig. 5. Proposed motor drive model. TABLE II TRANSDUCER CLASSIFICATION No.
Description
Meaning
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Speed Value Temperature Value Torque Value Current 1 Value Current 2 Value Current 3 Value Current 4 Value Speed Configuration Global Warning Warning max. Speed Warning max. Temp. Warning max. Torque Warning max. Current 1 Warning max. Current 2 Warning max. Current 3 Warning max. Current 4
Sensor Sensor Sensor Sensor Sensor Sensor Sensor Actuator Event sequence sensor Event sequence sensor Event sequence sensor Event sequence sensor Event sequence sensor Event sequence sensor Event sequence sensor Event sequence sensor
Channel type key 0 0 0 0 0 0 0 1 2 2 2 2 2 2 2 2
V. EVALUATION OF THE PROPOSED SYSTEM An experimental test rig has been used for implementing real time applications based on the electrical drive, and testing the operation of the proposed IEEE1451 compatible EV’s propulsion drive. Also, a personal computer is used to emulate the ECU of the EV. A scheme of the complete system is shown in Fig. 6. The test–rig is based on a conventional 36 slots, 2 pairs of poles, 10kW 3–phase induction machine whose stator has been rewound to
4
construct a 36 slots, 3 pairs of poles, dual 3–phase induction machine. Two sets of stator 3–phase windings spatially shifted by 30 electrical degrees have been included. Two Semistack–IGBT modules from Semikron Inc. (serie SKS21F) have been used to drive the machine [23]. Each module includes a pre charge circuit, handles up to 21 amperes, and allows a maximum switching frequency of 15 kHz. Speed is also measured using a two channel, 10000 pulses per revolution, Herrekor incremental encoder (serie GHM5_S6). Moreover, an interface and a control boards have been designed and implemented to control the real system. The interface board is used to adapt analog signals provided by current sensors (two LEM 55–P Hall– effect current sensors included in each Semistack to measure two phase currents, four current sensors for control purposes), and the DC–link voltage. The encoder and power switches control signals are also optocoupled in this board, which includes a conventional protection circuit designed to maintain system integrity against fault conditions. The NCAP has been developed using a PC for testing purposes, while the proposed smart transducer module (STIM) is programmed on a PIC16F876, featuring the IEEE1451.2 compliant interface [24]. The propulsion drive control system is based on the TMS320LF28335 Texas Instruments digital signal processor (DSP) and the MSK28335 system [25]. It is electronically connected with the STIM using the SPI channel. This DSP provides peripheral for real time control of power systems. For instance, it includes up to twelve PWM outputs that be used to control two independent 3–phase voltage source inverters (VSI), including programmable dead time control systems. A peripheral for processing signals coming from a quadrature encoder in order to help the user to obtain the mechanical speed, and a high–performance 16 channels, 12–bits each one, analog–to–digital converter with up to 12.5 MSPS of conversion rate are also provided. A real–time implementation analysis has been done to prove the viability of the proposed IEEE 1451 compliant propulsion drive, Fig. 7. The step response of the motor is analyzed to evaluate the effects caused by the addition of the STIM (notice that the SPI channel in the DSP must be programmed to attend the STIM). The analysis of the system shows that the overload due to the application of the IEEE1451 standard is about 4ms. Notice that the speed response time of the electromechanical system is about 200ms. Consequently, the delay introduced by the standard is negligible. The system overload is estimated about 2 %, not having any practical effects on the performance of the propulsion drive. The degradation of the presented module is limited by the IEEE1451.2 architecture. Notice that other standards of the IEEE1451 family, like the IEEE1451.6, may introduce higher CPU overload due to the applied 258
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5
DUAL THREE-PHASE INDUCTION MOTOR
POWER ELECTRONIC CONVERTER A
B
Main switch
a b c d e f
Speed Encoder Drivers Diagnostics
Hall effect current sensor
Smart transducer Interface Module SPI Channel TII
DSP TMS320LF28335
Alarm signal
Car computer Module
Analog Interface
CONTROL BOARDS
PIC16F876 EV Propulsion Drive
Fig. 6. Scheme of the experimental environment.
interface (CAN bus). The main aim of this work is to help the development and use of Intelligent Vehicle Safety Systems that use information & communication technologies to increase road safety, reducing the number of accidents. Taking into account that probably one of the most important electronic equipments for the active security in a vehicle is the propulsion module, and that a common driver reaction to visual or auditory stimuli can be averaged between 150 and 190ms, the proposed IVN system architecture is valid for the propulsion module of a vehicle.
degraded (time delay caused by IEEE1451 architecture), this degradation is reduced against previous works due to the use of the IEEE1451.2 Std. From the observations make during the experiments, it can be deduced that the transformation of the propulsion module in an IEEE 1451 compliant system has very little effect on the performance of the real–time application. An additional microcontroller is used to implement the STIM, increasing the cost of the overall system. However, the reduction in the replacement cost of an IEEE1451–based system is expected to compensate the original increasing cost because the IEEE 1451 standard offers a very effective architecture to implement inexpensive modules for large–scale production. ACKNOWLEDGMENT The authors gratefully acknowledge the Spanish Government for the economical support provided within the National Research, Development and Innovation Plan, under references DPI2005/04438 and DPI2007/60128. REFERENCES [1] [2]
Fig. 7. Experimental test for the evaluation of the IEEE1451 system overload.
VI. CONCLUSIONS This paper describes the design of an IEEE1451–based smart module that accomplishes the propulsion of an EV. The proposed module is independent of transducers’ communication protocols, and it is based on a hierarchical architecture where the EV propulsion module is autonomous. Although the drive performance obtained is
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[4]
[5]
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