• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.145-154
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• 2009

The main goal of this paper is to develop a methodology for increasing the reliability of truck OD matrices in Seoul Metropolitan Area. We propose a Hybrid Method made up of five processes by using Non-Traffic Assignment and Gradient Method. A Hybrid Method and Gradient Method have applied for comparison and estimation in Seoul Metropolitan Area. Mean Error and Root Mean Square Error of a Hybrid Method present lower than Gradient Method. The findings of this paper show that the new truck OD matrices created by a Hybrid Method are more reliable than the existing truck OD matrices in the Seoul Metropolitan Area.

• Structural Engineering and Mechanics
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• v.77 no.6
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• pp.809-817
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• 2021

In this study, the dynamic behavior of a three-span hybrid continuous arch bridge under vehicle loading is investigated. The natural vibration characteristics of the bridge were analyzed through pulsation test. In the dynamic loading test, the vibrations of the bridge under different truck speeds and different pavement conditions were tested, and time histories of deflection and acceleration of the bridge were measured. Based on the dynamic loading test, the impact coefficient was analyzed. The results indicate that the pavement smoothness had more impacts on the vibration of the bridge than the truck's speed. The vertical damping of the bridge under the excitation of the trucks is larger than the transverse damping. Resonance occurs at the side span of the bridge under a truck at 10 km/h.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1080-1085
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• 2005

A hybrid control scheme is proposed for the stabilization of backward movement along simple paths for a vehicle composed of a truck and six trailers. The hybrid comprises the combination of a linear quadratic regulator (LQR) and a neurocontroller (NC) that is trained by a genetic algorithm (GA). Acting singly, either the NC or the LQR are unable to perform satisfactorily over the entire range of the operation required, but the proposed hybrid is shown to be capable of providing good overall system performance. The evaluation function of the NC in the hybrid design has been modified from the conventional type to incorporate both the squared errors and the running steps errors. The reverse movement of the trailer-truck system can be modeled as an unstable nonlinear system, with the control problem focusing on the steering angle. Achieving good backward movement is difficult because of the restraints of physical angular limitations. Due to these constraints the system is impossible to globally stabilize with standard smooth control techniques, since some initial states necessarily lead to jack-knife locks. This paper demonstrates that a hybrid of neural networks and LQR can be used effectively for the control of nonlinear dynamical systems. Results from simulated trials are reported.

• Tribology and Lubricants
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• v.29 no.5
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• pp.310-317
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• 2013

To reduce vehicle fuel consumption due to not only driving but also air conditioning, battery-operated non-starting conditioning systems with thermoelectric modules and without mechanical elements like compressors are being manufactured for use by hybrid heavy trucks in the near future. In this study, the voltage and current consumed by a thermoelectric module were measured to determine the required battery power, and the performance of the conditioning system with air temperature, and humidity of the inlet/outlet modules and inside/outside the cabin for a truck, was evaluated using experimental apparatus under actual conditions. The results showed that, the thermoelectric module can be continously operated for about 1.5 h using existing 24 V batteries. The coefficent of performance(COP) of the cooling and heating modes was calculated to be an average 0.8-1.32. As expected, the heating performance was 30% more efficient than the cooling performance, which is general characteristic of thermoelectric modules.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.51 no.2
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• pp.99-104
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• 2002

In this paper, we construct a hybrid intelligent controller based on a fusion scheme of GA(Genetic Algorithm) and FCM(Fuzzy C-Means) clustering-based ANFIS(Adaptive Neuro-Fuzzy Inference System). In the structure identification, a set of fuzzy rules are generated for a given criterion by FCM clustering algorithm. In the parameter identification, premise parameters are optimally searched by adaptive GA. On the other hand, consequent parameters are estimated by RLSE(Recursive Least Square Estimate) to reduce the search space. Finally, we applied the proposed method to the truck backer-upper control and obtained a better performance than previous works.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.433-439
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• 1998

In this paper, we present an approach to the structure identification based on the input space partition methods and to the parameter identification by hybrid learning method in neuro-fuzzy system. The structure identification can automatically estimate the number of membership function and fuzzy rule using grid partition, tree partition, scatter partition from numerical input-output data. And then the parameter identification is carried out by the hybrid learning scheme using back-propagation and least squares estimate. Finally, we sill show its usefulness for neuro-fuzzy modeling to truck backer-upper control.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2314-2316
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• 2000

In the construction of successful fuzzy models and/or controllers for nonlinear systems, identification of a good fuzzy Neural inference system is an important yet difficult problem, which is traditionally accomplished by trial and error process. In this paper, we propose a systematic identification procedure for complex multi-input single- output nonlinear systems with DNA coding method.DNA coding method is optimization algorithm based on biological DNA as are conventional genetic algothms (GAs). We also propose a new coding method for applying the DNA coding method to the identification of fuzzy Neural models. To acquire optimal TS fuzzy model with higher accuracy and economical size, we use the DNA coding method to optimize the parameters and the number of fuzzy inference system.

• Journal of Biosystems Engineering
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• v.37 no.3
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• pp.148-154
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• 2012

Purpose: In order to improve road-friendliness of heavy vehicles, a fuzzy hybrid control strategy consisting of a hybrid control strategy and a fuzzy logic control module is proposed. The performance of the proposed strategy should be effectively evaluated using a hardware-in-the-loop (HIL) simulation model of a semi-active suspension system based on the fuzzy hybrid control strategy prior to real vehicle implementations. Methods: A hardware-in-the-loop (HIL) simulation system was synthesized by utilizing a self-developed electronic control unit (ECU), a PCI-1711 multi-functional data acquisition board as well as the previously developed quarter-car simulation model. Road-friendliness of a semi-active suspension system controlled by the proposed control strategy was simulated via the HIL system using Dynamic Load Coefficient (DLC) and Dynamic Load Stress Factor (DLSF) criteria. Results: Compared to a passive suspension, a semi-active suspension system based on the fuzzy hybrid control strategy reduced the DLC and DLSF values. Conclusions: The proposed control strategy of semi-active suspension systems can be employed to improve road-friendliness of road vehicles.

• Transactions of the Korean Society of Automotive Engineers
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• v.25 no.1
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• pp.103-110
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• 2017

Most commercial vehicles have adopted the hydraulic power steering system. To reduce fuel consumption and to improve steering controllability, a hybrid electric power steering system is being developed for commercial vehicles. In this study, the HILS (Hardware In the Loop Simulation) system equipped with a commercial vehicle hybrid electric power steering system was developed and the vehicle dynamic performance of a truck with the steering system was evaluated. The hybrid electric power steering system is composed of the EHPS motor pump, column mounted EPS system, and ball nut steering gear box for heavy commercial vehicles. The accuracy of vehicle models equipped with the HILS system was verified with comparisons between the simulation results and field test results. The road reaction forces of the steering system were generated from the vehicle model and verified using field test results. Step steering tests using the verified HILS system were carried out and the performance of a newly developed commercial vehicle hybrid electric power steering system was evaluated.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.20-25
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• 2021

This paper is the result of a research on hybrid tuning technology developed to improve the actual fuel efficiency and reduce emissions of in-use light-duty diesel trucks. In this study, a hybrid powertrain was constructed by inserting an electric motor between the diesel engine and manual transmission of an internal combustion engine vehicle and installing a battery. To verify the safety, a test was conducted based on the Korean tuning regulations. In particular, since there has been no case of tuning an internal combustion engine vehicle into a hybrid vehicle in Korea, it was necessary to carry out all procedures to receive tuning approval. The approval process consists of a technical review, safety verification test, and application for tuning approval. As a result, the test vehicle was approved for tuning because both the technical review and vehicle test results were suitable. Therefore, this study confirmed the safety of diesel hybrid tuning technology, and laid the foundation for the research and development of technologies to tune into an eco-friendly vehicle as well as the activation of related industries.