• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.10-13
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• 2010

저상 굴절 차량에는 전차륜 시스템이 요구되며, AWS ECU는 전차륜 시스템의 핵심적인 역할을 하는 전자 제어 장치이다. 실제 차량 주행을 위해서는 차량에 따른 ECU의 설정 값 변경이 필요하며, 현재 ECU의 동작 상태를 점검할 수 있는 기능이 요구된다. 이러한 기능을 수행하기 위하여 ECU에 서비스 루틴을 추가하고, 진단 프로그램을 개발하여 성능을 평가하였다.

• Journal of the Korean Society for Railway
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• v.10 no.4
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• pp.444-450
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• 2007

The bi-modal tram guided by the magnetic guidance system has two car-bodies and three axles. Each axle of the vehicle has an independent suspension to lower the floor of the car and improve ride quality. The turning radius of the vehicle may increase as a consequence of the long wheel base. Therefore, the vehicle is equipped with the All-Wheel-Steering(AWS) system for safe driving on a curved road. Front and rear axles should be steered in opposite directions, which means a negative mode, to minimize the turning radius. On the other hand, they also should be steered in the same direction, which means a positive mode, for the stopping mode. Moreover, only the front axle is steered for stability of the vehicle upon high-speed driving. In summary, steering angles and directions of the each axle should be changed according to the driving environment and steering mode. This paper proposes an appropriate AWS control algorithm for stable driving of the bi-modal tram. Furthermore, a multi-body model of the vehicle is simulated to verify the suitability of the algorithm. This model can also analyze the different dynamic characteristics between 2WS and AWS.

• Journal of the Korean Society for Railway
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• v.11 no.3
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• pp.225-232
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• 2008

AWS (all wheel steering) is applied to improve the stability and the turning performance. Most automotive cars are mainly controlled by FWS (front wheel steering) system except some cars which are made to improve their stability by using AWS. Articulated vehicles with a pivoting joint for easy turn are difficult to make a sharp turn because of the long body and long wheelbase. Therefore applying AWS to the articulated vehicles is effective to reduce the turning radius. The AWS control method for the articulated vehicles is currently applied to only Phileas vehicles which were developed by APTS. The paper on the design of a controller to guide an articulated vehicle along the path was published but control algorithm for manual driving has not been reported. In the present paper, steering, characteristics of the Phileas vehicles have been analyzed and then new algorithm has been proposed. To verify the AWS algorithm, Commercial S/W, ADAMS was used for validity of the dynamic model and algorithm.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.3
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• pp.240-249
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• 2013

This paper discusses the maneuvering control algorithm based on all-wheel independent driving and steering control techniques for special purpose 6WD/WS vehicles. The maneuvering control algorithms considering superior dynamic characteristics of high power in-wheel motors and independent steering system are designed to perform driving, steering, vehicle stability, and fault tolerant control. The maneuvering controller applies sliding and optimal control theories considering optimal torque distribution and friction circle related to the vertical tire force. The fault tolerant control algorithm is applied to obtain the similar maneuverability to that of the non-faulty vehicle. The simulations using the Matlab/Simulink dynamics model and experiments using HIL simulator mounting the real controllers with the designed control algorithms prove the improved performances in terms of vehicle stability and maneuverability.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.6
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• pp.1229-1238
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• 2011

This paper deals with the lateral dynamic model of an all-wheel steered articulated vehicle to design a guidance controller. Nonlinear dynamic model of articulated vehicle is developed by complementing the model about the BRT system of California PATH in U. S. A. and the Phileas system of the APTS in Netherlands. Linear lateral dynamic model has been derived from the nonlinear dynamic model under some assumptions associated with the driving conditions. To design a guidance controller, we derive a transfer function that is steering angle as input and lateral acceleration as output from the linear lateral dynamic model by applying the parameter of vehicle that is developed by Korea Railroad Research Institute. To validate the dynamic model, nonlinear dynamic model has been compared with a vehicle model that has been programmed in ADAMS, and linear dynamic model has been compared with a nonlinear dynamic model under sime assumptions.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1717-1725
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• 2008

In this paper, the HILS system is proposed for the AWS ECU of the bi-modal tram. Using the HILS of the AWS ECU, the behavior of the vehicle can be predicted and the reliability of the AWS system also can be verified. The hardware part of the HILS system includes the ECUs, hydraulic systems, steering linkages and sensors of the bi-modal tram. The software part of the HILS system contains the virtual vehicle model and sensor emulation. Driver input conditions, such as vehicle velocity and front steering angle, are provided to the ECUs by the software. The driving simulation of the bi-modal tram is carried out by the HILS. Also, the reliability of the AWS system, including the ECUs and hydraulic systems, is verified.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1231-1236
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• 2008

Since the bi-modal tram is too long so that the traditional steering system controlled only the first axle increases its turning radius, it is not suitable to the domestic road environment. In addition, it become hard to make fine parking with the traditional steering system. To resolve the problem, the bi-modal tram requires an all wheel steering system (AWS) that the second axle is controlled by the first axle's degree and the velocity of vehicle, and the third axle is steered by the articulation angle's degree and the velocity of degree. This paper addresses the factors for the AWS ECU design, the strategies to solve the problems, the core technologies for the implementation, and also the outcomes and analysis of the performance evaluation of implemented system.

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.5
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• pp.84-90
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• 2009

The bi-modal tram is under development as a new public transportation. The features of the tram are an extended wheel base and its length. This features result in difficulties for drivers on maneuvering the tram. Therefore, the all wheel steering system is applied to the articulated vehicle. The AWS system enables the vehicle to steer all the rear wheels independently and improves its driving characteristics. However, the bi-modal tram has a problem to move backward in the limited place because of its geometric feature and the AWS system. Hence, the reverse parking assistant algorithm for articulated vehicle is developed to solve the problems of the reverse parking. Using the vehicle model which includes the reverse parking assistant algorithm, the dynamic analysis is performed for several parking cases. By the result of the analysis, the stability and validity of the reverse parking assistant algorithm is verified.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.99-108
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• 2007

The bi-modal tram guided by the magnetic guidance system has two car-bodies and three axles. Each axle of the vehicle has an independent suspension to lower the floor of the car and improve ride quality. The turning radius of the vehicle may increase as a consequence of the long wheel base. Therefore, the vehicle is equipped with the All-Wheel-Steering(AWS) system for safe driving on a curved road. Front and rear axles should be steered in opposite directions, which means a negative mode, to minimize the turning radius. On the other hand, they also should be steered in the same direction, which means a positive mode, for the stopping mode. Moreover, only the front axle is steered for stability of the vehicle upon high-speed driving. In summary, steering angles and directions of the each axle should be changed according to the driving environment and steering mode. This paper proposes an appropriate AWS control algorithm for stable driving of the bi-modal tram. Furthermore, a multi-body model of the vehicle is simulated to verify the suitability of the algorithm. This model can also analyze the different dynamic characteristics between 2WS and AWS.

• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.1
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• pp.144-151
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• 2008

The bi-modal vehicle is composed of two car-bodies and three axles. Each axle of the vehicle has an independent suspension and all wheels are steerable. Since the bi-modal vehicle has longer wheelbase than most urban buses, the All-Wheel-Steering(AWS) system is adapted for to ensure safe driving and proper turning radius on a curved road. This paper proposes an AWS control algorithm for stable driving of bi-modal vehicle. Steering angles and directions of each axle of bi-modal vehicle changed according to the driving environment and steering modes. In the case that front and rear axles should be steered in opposite directions is a negative mode, and the other case that the axles should be steered in the same direction is a positive mode. For example, in the positive mode, front and real axles are steered in the same direction, while in the negative mode, they are steered in the opposite direction. A multibody model of the vehicle is used to verify the performance of the steering algorithm and simulation results of 2WS are compared with those of AWS under the same condition.