Decentralized neuro-fuzzy control for half car with semi-active suspension system

In this paper, a decentralized neuro-fuzzy controller has been created in order to improve the ride comfort and increase the stability for half car suspension system, which used the magneto-rheological damper as a semi-active device. Firstly, relative gain array and relative disturbance gain methods have been used for deriving a relation between inputs, disturbances and outputs to select pairing with minimum interaction to design a decentralize controller. Secondary, decentralized neuro-fuzzy controllers for front and rear chassis are designed to predict the required damping force taking the acceleration of the sprung mass and desired acceleration obtained by using pole-placement method as inputs. To predict the control voltage required for producing the force predicted by the controller, the inverse neuro-fuzzy model of MR damper has been designed. Simulation by using MATLAB programs has been created. The results show that the ride comforts and vehicle stability have been improved in comparison with the passive system.     

New metal fitting geometry and optimization of the swaging parameters for an automobile power steering hose

To solve the power steering (PS) hose oil leakage problem in automobile applications, a new geometry design of the metal fitting is required, and the swaging conditions applied to the PS hose should be optimized. In this study, a new metal fitting geometry for the PS hose was proposed. A CAE simulation for both the proposed and the conventional metal fittings was conducted, and both the stress and the strain in the PS hose were compared. An experimental verification was also performed with these two different metal fittings. Additionally, the swaging conditions were optimized by the durability cycle time, which was measured in an impulse test of the swaged PS hose. For a more economical production, practical working conditions were also recommended and experimentally verified.     

Simplified dynamics model for axial force in tripod constant velocity joint

Tripod constant velocity (TCV) joints are common components in automotive and mechanical applications. The benefits of the TCV joint are its high plunge capacity and high torque capacity. During power transmission, the friction inside the joint generates an axial force according to the kinematics. This force causes noise and vibration problems. In this study, a simplified multi-body dynamic model based on a phenomenological TCV joint friction model is developed. This model considers the generated axial force (GAF) of a TCV joint with different lubricate conditions. The efficiency and accuracy are verified by comparison with other prediction models and experiments. Thus, this model can be used to design and control the manufacture process of TCV joints.     

Efficiency improvement for an unthrottled SI engine at part load

Variable valve timing (VVT) and cylinder deactivation (CDA) are promising methods in reducing fuel consumption and emission at part load in SI engines. An SI engine which uses electromagnetic valvetrain (EMV) will eliminate flow restriction from the throttle valve and produce higher indicated mean efficiency pressure (IMEP) due to the disabling of some of the working cylinders at part load. Therefore, pumping loss can be significantly reduced at part-load conditions. In addition, duration and timing of valve events are variably controlled at different operating conditions. This contributes to the improvement of engine efficiency. In this study, a dynamic model of an unthrottled SI engine has been developed to simulate the engine cycle. The model uses an EMV system that allows valvetrain control and cylinder deactivation techniques to be carried out in simulation flexibly. The simulated results find the optimal valve timing for different engine speeds. The optimal timing of intake valve closing depends on engine speed linearly, while the intake valve opening insignificantly influences engine performance. Additionally, this study also shows that cylinder deactivation modes can be successfully applied in improving engine efficiency at different engine loads. Different cylinder deactivation strategies have been applied for the full range of engine loads. It is concluded that the two-cylinder deactivation mode (50% CDA) considerably improves fuel consumption at low engine load. Meanwhile, one-cylinder deactivation (25% CDA) is an optimal fuel economy mode at medium engine load. With proper uses of VVT and CDA strategies, the efficiency of an SI engine can be increased more than 30% at low engine load and 11.7 % at medium engine load.     

Road identification in monocular color images using random forest and color correlogram

This paper presents a system to identify road and non-road regions from monocular color images of paved and unpaved roads. Despite being a single object, the road in these images is subject to large changes in appearance due to environmental effects and track materials. This condition has challenged the practical application of road identification. The proposed system combines random forest with color correlogram to overcome such conditions and offers a classifier for road and non-road regions in traffic images. As a color feature, the color correlogram depicts the spatial correlation of color changes in an image. Using random forest, road identification is formulated as a learning paradigm. The combined effects of color correlograms and random forest create a robust system capable of identifying roads even in variable situations in real time. This combination is more effective than other combinations, such as a color histogram plus random forest, a color correlogram plus neural network, or a color histogram plus neural network.     

Development of a new analytical model for a railway vehicle equipped with independently rotating wheels

The urban tram introduced recently has a low-floor structure for the convenience of passengers getting on and off. To adjust the low-floor level and improve performance on curves, most low-floor trams have IRWs (independently rotating wheels) with no central axle between the two wheels. Eliminating the central axle, however, creates several inherent problems, such as insufficient guiding force and excessive wear. To analyze these problems, a new analytical model is described in this paper to describe the dynamic characteristics of IRWs more precisely. This analytical model is developed to consider the effects of longitudinal creep in particular, which have been ignored in conventional analytical models of IRWs. In addition, a running stability analysis based on the newly developed analytical model is conducted to compare the critical speeds of IRW-axle vehicles and rigid-axle vehicles. The dynamic characteristics of an initial disturbance are compared to verify that the analytical model is effective in expressing the dynamic characteristics of IRWs.     

Development of an electric booster system using sliding mode control for improved braking performance

Brake systems of the future, including BBW (Brake-by-Wire), are in development in various forms. In one of the proposed hydraulic BBW systems, an electric booster system replaces the pneumatic brake booster with an electric motor and a rotational-to-linear motion mechanism. This system is able to provide improved braking performance by the design of controllers with precise target pressure tracking and control robustness for better system reliability. First, a sliding mode controller is designed using the Lyapunov function approach to secure the robustness of the system against both the model uncertainty and the disturbance caused by the master cylinder and mechanical components. Next, a simulation tool is constructed to validate the electric booster system with the proposed controller. Finally, the electric booster system is implemented into an actual brake ECU and installed in a vehicle for testing under various braking conditions. The experimental results demonstrate that the proposed controller produces faster pressure build-up performance than the conventional brake system, and its tracking performance is sufficient to ensure comfortable braking.     

Power control strategy for preventing thermal failure of passively cooled automotive battery packs

Safety mechanism is required for an automotive battery pack to prevent thermal failure which could lead to catastrophic events. Passively cooled battery packs can prevent thermal failure by conducting adaptive control of battery power without any external cooling device. The key to this power control is how to secure battery safety while minimizing energy loss. This paper proposes a novel, adaptive power control strategy for automotive passive-cooling battery packs. Four different cases with electrochemical battery model are simulated and compared to each other according to a city driving profile. Driving simulation result confirmed that the present power control algorithm is an effective solution for preventing thermal failure along with improving energy efficiency of automotive battery packs.     

Design and development of automotive blind spot detection radar system based on ROI pre-processing scheme

In the conventional 2D-FFT based target detection method, all range-Doppler cells are computed by FFT (Fast Fourier Transform) and scanned by CA-CFAR (Cell-Averaging Constant False Alarm Rate) detection. This results in high computational complexity and long processing time. In this paper, we developed an automotive 24 GHz BSD (Blind Spot Detection) FMCW (Frequency Modulated Continuous Wave) radar with a low complexity target detection architecture based on a ROI (Region Of Interest) pre-processing scheme. In the real BSD zone, because the number of cars to be detected is limited, the designed method only extracts their velocities corresponding to the range ROIs in which real targets exist. Moreover, the presence probability of vehicles with the same range-bin but different velocities is very low. Thus, in the designed method, some Doppler ROIs cells with a high magnitude are only applied for CA-CFAR detection. This architecture can dramatically reduce the amount of data to be processed compared to that of the conventional 2D FFT based method, resulting in enhanced processing time. We developed a 24 GHz FMCW radar system composed a transceiver, antennas, and signal processing module. The designed algorithm was implemented in a tiny micro-processor of the signal processing module. By implementing our proposed algorithm in the developed 24 GHz FMCW radar system in an anechoic chamber and a real road, we verified that the range and velocity of a car occupying the BSD zone were detected. Compared to that of the conventional method, the reduction ratio of the total processing time was measured to be 52.4 %.     

Probe vehicle lane identification for queue length estimation at intersections

Vehicles instrumented with Global Positioning Systems, also known as GPS probe vehicles, have become increasingly popular for collecting traffic flow data. Previous studies have explored the probe vehicle data for estimating speeds and travel time; however, there is very limited research on predicting queue dynamics from such data. In this research, a methodology was developed for identifying the lane position of the GPS-instrumented vehicles when they are standing in the queue at signalized intersections with multiple lanes, particularly in the case of unequal queue. Various supervised and unsupervised clustering methods were tested on data generated from a microsimulation model. Among the tested methods, the Optimal Bayes Rule that utilizes probability density functions estimated using bivariate statistical mixture models was found to be effective in identifying the lanes. The methodology for lane identification was tested for queue length estimation. This research confirms that the lane identification is an important step required prior to the queue length estimation. The accuracies of the models for lane identification and queue length estimation were evaluated at varying levels of demand and probe vehicle market penetrations. In general, as the market penetration increases, the accuracy improves as expected. The result shows that 40% market penetration rate is adequate to reach about 90% accuracy.