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In this paper we present the concept of green routing or eco routing and how one would implement this using attributes defined in real time traffic information and digital road map. The routing referred to this paper applies mainly to road networks where one wants to get from point A to point B by minimizing the fuel consumed in a vehicle. The new model of speed profile prediction which yields stop and go speed at the start, end and zero of the acceleration under sub-node and link conditions is described. The results for the lowest fuel consumption show about 8.5% of simulated routes and 5% (9%) of vehicle test routes saving in fuel, when compared to that for the existing route planning course (recommended and short distance route), even traveling time about 10% longer time. These results clearly show prediction accuracy of fuel consumption between modeling and measurement is below the average about 12%.

Electric Power Steering (EPS) needs to meet both functional and stability requirements, it plays significant role in controlling vehicle motion. In the meantime, customers emphasizes natural steering feel which can reflect vehicle motion and road surface information while isolate unwanted external disturbances. In general, conventional EPS control algorithms exert assist torque according to driver torque measured from torque sensor, while maintaining stability using stabilizing compensator. However, there exist significant trade-off between steering feel and stability, because the performances of assist torque control and stabilizing compensator are strongly coupled. In this paper a torque feedback control algorithm for EPS system is proposed in order to overcome the trade-off, and to achieve more natural, robust steering feel.

Shudder vibration of a hydraulic power steering system during parking maneuver was studied with numerical and experimental methods. To quantify vibration performance of the system and recognize important stimuli for drivers, a shudder metric was derived by correlation between objective measurements and subjective ratings. A CAE model for steering wheel vibration analysis was developed and compared with measured data. In order to describe steering input dependency of shudder, a new dynamic friction modeling method, in which the magnitude of effective damping is determined by average velocity, was proposed. The developed model was validated using the measured steering wheel acceleration and the pressure change at inlet of the steering gear box. It was shown that the developed model successfully describes major modes by comparing the calculated FRF of the hydraulic system with measured one from the hydraulic excitation test.

The automotive industry’s journey towards fully autonomous vehicles brings more and more vehicle control systems. Additionally, the reliability and robustness of all these systems must be guaranteed for all road and weather conditions before release into the market. However, the ever-increasing number of such control systems, in combination with the number of road and weather conditions, makes it unfeasible to test all scenarios in real life. Thus, the performance and robustness of these systems needs to be proven virtually, via vehicle simulations. The key challenge for performing such a range of simulations is that the tire performance is significantly affected by the road/weather conditions. An end user must therefore have access to the corresponding tire models. The current solution is to test tires under all road surfaces and operating conditions and then derive a set of model parameters from measurements.

Road friction estimation algorithms had been studied for many years because it is very important factor for safety control and fuel efficiency of vehicle. But traditional solutions are hard to adapt in automotive industry because their performance is not sufficient enough and expensive to implement. Therefore, this paper proposes a road friction estimation algorithm based on a trained artificial neural-network which is low cost and robust. The suggested method doesn’t need expensive additional sensors such as optical or lidar sensor, also it shows better performance in real car environment compared to other algorithms based on vehicle dynamics. In this paper, we would describe this algorithm in detail and analyze the test results evaluated in real road conditions.

The engine indicated torque is not delivered entirely to the wheels, because it is lowered by losses, such as the pumping, mechanical friction and front auxiliary power consumption. The front auxiliary belt drive system is a big power consumer-fueling and operating the various accessory devices, such as air conditioning compressor, electric alternator, and power steering pump. The standard fuel economy test does not consider the auxiliary driving torque when it is activated during the actual driving condition and it is considered a five-cycle correction factor only. Therefore, research on improving the front end auxiliary drive (FEAD) system is still relevant in the immediate future, particularly regarding the air conditioning compressor and the electric alternator. An exertion to minimize the auxiliary loss is much smaller than the sustained effort required to reduce engine friction loss.

The integrated control system of Electronic Stability Control (ESC) and Motor-Driven Power Steering (MDPS) improves vehicle performance and extends functions via CAN network without any hardware modification. Although the ESC and MDPS integrated system does not improve vehicle behavior directly, it can inspire drivers to steer to the right direction by changing steering torque assistance characteristics. There are two different ways to control both ESC and MDPS systems: Top-down and Parallel control mode. First, the Top-down control mode, which is already widely used on the market, imposes ESC on the additional functions of ESC+MDPS integrated system. On the contrary, the Parallel control mode distributes the functions to ESC and MDPS, therefore each system does their own role and cooperates on special events. In this study, the parallel control mode controller is proposed and compared with the Top-down control mode.

Reductions in powertrain noise have led to an increased proportion of road noise, prompting various studies aimed at mitigating it. Road excitation primarily traverses through the vehicle suspension system, necessitating careful optimization of the characteristics of bushings at connection points. However, optimizing at the vehicle assembly stage is both time-consuming and costly. Therefore, it is essential to proceed with optimization at the subsystem level using appropriate objective functions. In this study, the blocked force and energy-based index derived from complex power were used to optimize the NVH performance. Calculating the complex power in each bushing enables computing the power flow, thereby providing a basis for evaluating the NVH performance. Through stiffness injection, the frequency response functions (FRF) of the system can be predicted according to arbitrary changes in the bushing stiffness.

The thermoplastic automotive pulley has been developed and will be commercialized to high volume production that achieves cost saving and weight reduction over other automotive pulleys in the metal and thermosetting resin by Hyundai Motor Company. Design feature incorporated in this automotive pulley allow it to be manufactured and assembled onto the water pump more efficiently in consequence of design integration with the water pump and power steering pulley. However, the harsh environment and dynamic loads that the thermoplastic pulley has to withstand required extensive CAE analysis and testing of the molded parts and the standard glass reinforced PA was selected for the application to maximize cost savings. The key aspects of the plastic automotive pulley as well as its advantage are presented.

Future technology trends of commercial vehicle steering components can be divided into three types. Environment-friendly technologies for environment-related regulations such as reducing emissions and improving fuel efficiency, and technology for driving convenience using electric steering control systems, and safety technology to protect drivers, passengers, nearby vehicles and pedestrians. Heavy duty commercial vehicles require a high-power steering system that used engine-driven hydraulic pump systems (generally used min 120bar, 17Liter/min) compared to passenger cars. In recent technical trend, In order to improve fuel efficiency and realize autonomous driving technology, we designed EHPS and Motor driven electric control actuator with the same structure as C-EPS.

To predict structure-borne interior noise using CAE simulation, it is important to establish a model for both the noise and vibration transfer path, as well as the excitation source. In the passenger vehicle, powertrain and road induced loads are major input sources for NVH. This paper describes a process to simulate the structure-borne road noise to 150Hz. A measured road surface is used for input for the simulation. Road surface data, in the form of height vs. distance, is converted to enforced motions at the tire patch in the frequency domain for input to the vehicle system model. The input loads are validated by the comparison of wheel hub excursions. The ability of the CAE simulation model to predict interior acoustic responses is shown by the comparison of the simulation results with measured vehicle interior responses.

The steering system is a critical component for controlling a vehicle's direction. In the context of Advanced Driver Assistance Systems (ADAS) and autonomous vehicles, where drivers may not always be actively holding the steering wheel, early detection of precursor noise signals is essential to prevent serious accidents resulting from the loss of steering system functionality. It is therefore imperative to develop a device capable of early detection and notification of steering system malfunctions. Therefore, the current study aimed to quantify the noise levels generated within the Column-based Electric Power Steering (C-EPS) system of a D-segment sedan. To this end, we measured the uniaxial acceleration in nine noise-generating areas while simultaneously collecting data from three Controller Area Network (CAN) sources that are directly related to steering operation.

This paper summarizes the development of a wireless message from infrastructure-to-vehicle (I2V) for safety applications based on Dedicated Short-Range Communications (DSRC) under a cooperative agreement between the Crash Avoidance Metrics Partners LLC (CAMP) and the Federal Highway Administration (FHWA). During the development of the Curve Speed Warning (CSW) and Reduced Speed Zone Warning with Lane Closure (RSZW/LC) safety applications [1], the Basic Information Message (BIM) was developed to wirelessly transmit infrastructure-centric information. The Traveler Information Message (TIM) structure, as described in the SAE J2735, provides a mechanism for the infrastructure to issue and display in-vehicle signage of various types of advisory and road sign information. This approach, though effective in communicating traffic advisories, is limited by the type of information that can be broadcast from infrastructures.

The development of vehicles faces changes in many future flows. The vehicle’s power transfer systems are being changed from conventional types to Hybrid, Electric and Hydrogen vehicles. At this moment, the technology of EPS (Electric Power Steering) system has been expanding from a simple torque assist system to LKAS(Lane Keeping Assist System), PAP(Park Assist Pilot), ALCAS(Active Lane Change System), ADAS(Advanced Driver Assistance System). A good test bench is necessary for the evaluation of both hardware and control logics of EPS in these complexities of development process. Simultaneous Rig and HILS tests can be performed to check that the steering hardware system can perform to the concept of the development vehicle and develop EPS control logic performances. The hardware performance of the steering system might be evaluated based on measured friction and stiffness, taking into account various driving conditions.

All vehicles have some or all accessories such as alternators, air conditioner compressors, power steering pumps, and water pumps. These devices are mounted on the front of the engine and are powered by a pulley mounted on the front of the crankshaft. This power represents a parasitic loss and this loss is greater at higher engine speeds. To reduce the impact of the accessories on the engine, a two speed transmission that reduces the accessories speed at off-idle conditions was designed, implemented, and tested on several vehicles. The vehicles were tested for fuel economy on the Japanese 10.15 Mode driving cycle, the FTP75 city cycle, and the HWFET Highway Cycle. Results showed an average of 5% reduction in fuel consumption and a corresponding 5% in CO2 with no impact of accessory performance and vehicle drivability. Simulations with GT-Drive software was used to determine the optimum speed reduction and the threshold switching speed that maximizes fuel savings.

This paper describes a lateral disturbance estimator for an application to a Motor Driven Power Steering (MDPS)-based driving assistant system. A vehicle motion can be disturbed laterally by wind force or load from bank angle acting on the vehicle in the lateral direction. An MDPS-based driving assistant system can be used to reduce steering effort of a human driver in a driving situation with lateral disturbance. In designing the MDPS-based driving assistant system, the lateral wind disturbance should be estimated to determine an assistant torque. An estimator for the vehicle lateral disturbance estimation has been developed. The proposed estimator consists of two parts: a tire self-aligning torque estimator and the lateral disturbance estimator. The lateral disturbance estimator has been designed on the basis of a 2-DOF bicycle model with available sensor signals from the MDPS module. A numerical simulation has been conducted in order to evaluate the proposed estimator.

For a complete automotive HVAC system, it is desirable to keep good air quality control for the interior vehicle cabin. This experimental study for evaluating the CO2 concentration levels in a vehicle cabin was done on the roads in South Korea. Increasing levels of CO2 can cause a passenger to become tired, sleepy and cause headaches or discomfort. The study results shows that CO2 and fine dust concentration is a result of the number of passengers,_driving condition and HVAC user settings. The result from this investigation can be used to establish a development guide for air quality in a vehicle cabin.

Drivers continually require steering performance improvement, particularly in the area of feedback from the road. In this study, we develop a new electrically-assisted steering logic by 1) analyzing existing steering systems to determine key factors, 2) modeling an ideal steering system from which to obtain a desirable driver torque, 3) developing a rack force observer to faithfully represent road information and 4) building a feedback compensator to track the tuned torque. In general, the estimator uses the driver torque, assist torque and other steering system signals. However, the friction of the steering system is difficult to estimate accurately. At high speed, where steering feeling is very important, greater friction results in increased error. In order to solve this problem, we design two estimators generated from a vehicle model and a steering system model. The observer that uses two estimators can reflect various operating conditions by using the strengths of each method.

The mobility technique is used to analyze the transfer functions of road noise between the suspension and the body structure. In the previous analyses, the suspension system and the body structure are altogether modeled as subsystems in the noise transfer path. In this paper, the mobility between the suspension and the body structure is analyzed by the dynamic stiffness at the connecting points. The measured drive point acceleration FRF at the connecting point in the transfer path was used to estimate the contributions of subsystems. The vibration modes of tire, the acoustic noise of tire's interior cavity, the vibration modes of the car's interior room, and the vibrations of body structure and the chassis are also considered to analyze the coupling effects of the road noise. Analyzing the measured results, direction for modification of car components is suggested.

In general, the ride and handling characteristics of a vehicle are strongly dependent on chassis parameters that come from the kinematic and compliance properties of a suspension system. For ride comfort improvement of a compact SUV with increasing handling performance simultaneously, this research proposes a new quantitative approach by considering various driving maneuvers and road surfaces. Particularly, five different road surfaces were used for ride comfort analysis, and this analysis was performed for two different vehicle speeds on a cleat road profile and three different vehicle speeds on a rough road profile. The contribution analysis of a suspension and a seat structure to ride comfort was investigated in order to decide an optimal structural combination. It was shown that contribution of each factor is different according to road profiles and driving conditions respectively.