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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.

It is an important factor in electric vehicles to show customers how much they can drive with the energy of the remaining battery. If the remaining mileage is not accurate, electric vehicle drivers will have no choice but have to feel anxious about the mileage. Additionally, the potential customers have range anxiety when they consider Electric Vehicles. If the remaining mileage to drive is wrong, drivers may not be able to get to the charging station and may not be able to drive because the battery runs out. It is important to show the remaining available driving range exactly for drivers. The previous study proposed an advanced model by predicting the remaining mileage based on actual driving data and based on reflecting the pattern of customers who drive regularly. The Bayesian linear regression model was right model in previous study.

Recently, as part of the effort to enhance fuel efficiency and reduce costs for eco-friendly vehicles, the R-gearless system has been implemented in the TMED (P)HEV system. Due to the removal of the reverse gear, a distinct backward driving method needs to be developed, allowing the Electronic Motor (e-Motor) system to facilitate backward movement in the TMED (P)HEV system. However, the capability of backward driving with the e-Motor is limited because of partial failure in the high-voltage system of an R-gearless system. Thus, we demonstrate that it is possible to improve backward driving problems by applying a new fail-safe strategy. In the event of a high-voltage battery system failure, backward driving can be achieved using the e-Motor with constant voltage control by the Hybrid Starter Generator (HSG), as proposed in this study.

Recently, regulations on automobile emission have been significantly strengthened to address climate change. The automobile industry is responding to these regulations by developing electric vehicles that use batteries and fuel-cells. Automobile emissions are environmentally harmful, especially in the case of vehicles equipped with high-temperature and high-pressure diesel engines using compression-ignition, the proportion of nitrogen oxides (NOx) emissions reaches as high as 85%. Additionally, air pollution caused by particulate matter (PM) is six to ten times higher compared to gasoline engines. Therefore, the electrification of commercial vehicles using diesel engines could potentially yield even greater environmental benefits. For commercial vehicles battery electric vehicles (BEVs) require a large number of batteries to secure a long driving range, which reduces their maximum payload capacity.

Despite the widespread adoption of lithium-ion batteries in various applications such as energy storage, concerns related to thermal management have been persisting, primarily due to the heat generated during their operation and the associated adverse effects on its efficiency, safety, and lifetime. Hence, the thermal characterization of lithium-ion batteries is essential for optimizing the layout of the battery cells for a pack design and the corresponding thermal management system. This study focuses on an experimental investigation of heat generation of Li-ion batteries under different operating conditions, including charge-discharge rates, ambient temperatures, states of charge, and compressive pressure. The experiments were conducted using a custom-designed multifunctional calorimeter, enabling precise measurement of the heat generation rate of the battery and the entropy coefficient. The measured results have shown a good match with the calculated heat generation rate.

In this study, a novel selective matching logic for a wheel/tire is proposed, to decrease the vehicle driving vibration caused by wheel/tire non-uniformity. The new logic was validated through matching simulation/in-line matching evaluation. A theoretical radial force variation model was established by considering the theoretical model of the existing references and the wheel/tire assembly mechanism. The model was validated with ZF’s high-speed uniformity equipment, which is standard in the tire industry. The validity of the new matching logic was verified through matching simulation and mass production in-line evaluation. In conclusion, the novel logic presented herein was demonstrated to effectively decrease the radial force variation caused by the wheel/tire.

As data science technologies are being widely applied on various industries, the importance of data itself increased. A typical manufacturer company has a vast data set of products as 2D&3D drawing formats, but a common problem was that building a database from the 2D&3D drawings costs much, and it is hard to update the database after it once built. Also, it is high-cost job when the new factor researched and necessary to investigate the new factors on previously fixed or uploaded drawings. As new products are developed with time, these problems are getting more difficult. In this paper, an automated database building method using CATIA introduced and future probabilities are suggested. An aluminum wheel part was used as an example. An automated logic used CATIA V5’s VBA functions and was handled by python programming language.

This research addresses the pressing need for reducing vehicle aerodynamic resistance, with a specific focus on mitigating wheel and tire resistance, which constitutes approximately 25% of the overall vehicle drag. While the prevailing method for reducing resistance in mass production development involves wheel opening reduction, it inadvertently increases wheel weight and has adverse effects on brake cooling performance. To overcome these challenges, novel complementary resistance reduction methods that can be employed in conjunction with an appropriate degree of wheel opening reduction are imperative. In this study, we introduce symmetrical wheels with a fan-like shape as a solution. The fan configuration influences the surrounding flow by either drawing it in or pushing it out, depending on the direction of rotation. Application of these fan-type wheels to a vehicle's wheels results in the redirection of flow inwards or outwards during high-speed driving due to wheel rotation.

Lithium-ion battery has advantages of high energy density and cost effectiveness than other types of batteries. However due to the low mechanical stability, their performance is strongly influenced by environmental conditions. Especially, external pressure on a cell surface is a crucial factor because an appropriate force can improve battery cycle life, but excessive force may cause structural failure. In addition, battery pack is composed of various components so that uncertainties in dimension and material properties of each component can cause a wide variance in initial pressure. Therefore, it is important to optimize structural design of battery pack to ensure initial pressure in an effective range. In this paper, target stiffness of module structure was determined based on cell level cycle life test, then structural design has been optimized for weight reduction. Cell cycling tests were performed under different stiffness conditions and analyzed with regression model.

Platoon is a system that connects vehicles through vehicle-to-vehicle (V2V) communication technology to maintain a short distance between vehicles while driving on the road. To improve fuel efficiency, many automotive original equipment manufacturers (OEMs) are interested in developing and demonstrating real-world platoon system. However, it is hard for heavy duty trucks to develop this system due to the difficulty of maintaining the targeted intervehicle distance not only for fuel efficiency but also for safety in case of emergency braking. Because of this critical safety issue in the emergency situation, the platoon system for heavy duty trucks can be hardly demonstrated or tested in real vehicle environment. The relatively complex system and the slow response characteristic of commercial vehicles makes this even more difficult.

Recently, increasing system complexity and various customer demands result in the need for highly efficient vehicle development processes. Once the brake torque is predicted accurately during the driving scenario in the earlier stage, it will be able to prevent the changing the vehicle or brake system design to satisfy the legal regulation and customer requirement. As brake torque performance target allocate brake pad friction coefficient level and characteristic, the accurate friction coefficient prediction should be preceded for accurate prediction for brake torque. Generally, the friction coefficient of the brake pad is known to vary nonlinearly depending on the physical properties of the disc and the pad, as well as the brake disc rotational speed, the disc temperature, and the hydraulic pressure. Furthermore, it varies depending on the driving scenario even when other conditions are the same. Therefore, it is necessary to apply new methods to solve these challenges.

With the spread of new trends such as autonomous driving and vehicle subscription service, drivers may pay less attention to the maintenance of the vehicle. Brake pads being safety critical components, the wear condition of all service brakes is required by regulation to be indicated by either acoustic of optical devices or a means of visually checking the degree of brake lining wear [1]. Current application of the wear indicator in the market uses either sound generating metal strip or wire harness based pad wear sensor. The former is not effective in generating clear alarm to the driver, and the latter is not cost effective, and there is a need for more effective and low cost solution. In this paper, a pad wear monitoring system using MOC(Motor On Caliper) EPB(Electric Parking Brake) ECU is proposed. An MOC EPB is equipped with a motor, geartrain and an ECU. The motor current when applying the parking brake is influenced by the mechanical load at the brake pad side of the system.

Automotive OEMs have introduced a new development paradigm, modular architecture development, to improve diversity quality and production efficiency. It needs solid fundamentals of system-based performance evaluation and development for each system level and single component level. When it comes to NVH development, it is challenging to realize the modular concept because noise and vibration should be transferred through various transfer path consisting of many parts and systems, which interact with each other. It is challenging for a single system of interest to be evaluated independently of the adjacent parts and environments. In this study, a new system-based development process for a vehicle suspension was investigated by applying blocked force theory and FRF-based dynamic substructuring. The objective is to determine the better dynamic stiffness distribution of many bushes installed in a suspension system in the frequency range corresponding to road noise.

This paper presents an integrated control of in-wheel motor (IWM) and electronic limited slip differential (eLSD) to enhance the vehicle lateral stability and maneuverability. The two actuators are utilized in the proposed controller to achieve separate purposes. The IWM controller is designed to modify the understeer gradient for enhanced handling characteristic and maneuverability. The eLSD controller is devised to improve the lateral stability to prevent oversteer in a severe maneuver. The proposed controller consists of a supervisor, upper-level controller and lower-level controller. The supervisor determines a target motion based on a target understeer gradient for IWM control and a yaw rate reference for eLSD control. The upper-level controller generates a desired yaw moment for the target motion. In the lower-level controller, the desired yaw moment is converted to the control inputs for IWMs in the two front wheels and eLSD at the rear axle.

High-voltage battery system plays a critical role in eco-friendly vehicles due to its effect on the cost and the electric driving range of eco-friendly vehicles. In order to secure the customer pool and the competitiveness of eco-vehicle technology, vehicle electrification requires lowering the battery cost and satisfying the customer needs when driving the vehicles in the real roads, for example, maximizing powers for fun drive, increasing battery capacities for achieving appropriate trip distances, etc. Because these vehicle specifications have a critical effect on the high-voltage battery specification, the key technology of the vehicle electrification is the appropriate decision on the specification of the high-voltage battery system, such as battery capacity and power. These factors affect the size of battery system and vehicle under floor design and also the profitability of the eco-friendly vehicles.

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.

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 mass producible broad-band ANC system for road noise is developed with fully digital control system. For this configuration, installation packages are intensively considered by minimizing size of the controller, simplifying wiring system and implementing virtual microphone techniques. Virtual microphone technique enables error microphone to be installed in remote position of driver’s ear, and therefore, increases installation degree of freedom significantly. To enhance noise control performance with the minimum latency, filter design of FxLMS algorithm is optimized while additional audio compensation techniques are applied to maintain audio performance of amplifier. The present ANC system is equipped to HMC (Hyundai Motor Company) new release of hydrogen driven vehicle, which is introduced in the technology promotion event in Pyeongchang Olympic 2018.

In recent years, the emerging technology competitions in automotive industry are improving engine efficiency and electronizing for coping with stringent fuel-economy regulations. However, fuel-economy technologies such as engine down-sizing and numerous electronic parts entrust burden plastic materials acing as mainly electric insulation and housing to have to be higher performance, especially temperature endurance. Engineering plastics (EPs) have critical limitations in terms of degradation by heat. Heat-resisting additives in EP are generally used to be anti-degradation as activating non-radical decomposition of peroxide. However, it could not be effective way to impede the degradation in long term heat aging over 1,000 hours at high temperature above 180 °C. In this study, we suggested the new solution called ‘shield effect’ that is purposeful oxidation at the surface and local crystallization of EP to stop prevent penetrating oxygen to inside of that.

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.