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Based on the success of the second-generation Genesis G80 model, Hyundai Motor has declared the independence of Genesis as a luxury car brand in 2015. The third-generation G80 is the representative model of the Genesis brand and has a unique identity of Genesis that can surpass its competitors. In addition, it was necessary to develop seats that were considered not only for ICE but also for the scalability of electric vehicles. A newly formed Genesis organization established the Genesis design philosophy of its own. Four key elements of the design philosophy were comfort, aesthetics, usability and safety. The third-generation Genesis seats incorporate its design philosophy of seat design and new technologies based on comfort, aesthetics, usability, and safety. This paper describes the seat development of the Ergo Motion seat, Rear Seat Relaxtion(Relax + Position), Seat Syling, AVN switch display and PSS(pre-active safety seat )system, which are representative technologies.

The existing FCEV have been developed with only a few vehicle models. With the diversification of both passenger and commercial FCEV lineups, as well as the increasing demand for vehicle trailer towing, there is a growing need for high-capacity fuel cell stacks to be applied in vehicles. However, at the current level, there are limitations and issues that arise, such as insufficient power output and reduced driving speed. As a results, the importance of thermal energy management has been increasing along with the increase in required power. Traditional cooling performance enhancement methods have mainly focused on developing increased hardware specifications, but even this approach has reached its limitation due to package, cost and weight problem. Therefore, it is essential to develop a new cooling system to solve the increases in heat dissipation.

In this study it will show, big data analysis and user survey of driving records were conducted to investigate frequency of use and ease of operation of the regen paddle to control one-pedal driving system in electric vehicle. According to 3.8 million driving record big data analysis result, it was found that the driver manipulates 3.31 times on average during a single trip, mainly during the early stages of driving. According to user observation research result in 41.8% of participants did not used or used less than 5 time of regen paddle during one single trip. Also 336 participants, which occupy 83%, responded that the regen paddle manipulation for one-pedal driving was inconvenient. In conclusion, because of the use frequency of the regen paddle is low and the operation of regen paddle is inconvenient. It seems necessary to change the design of the regen paddle.

With the recent development of technologies for interpreting vibration and noise of vehicles, it has become possible for carmakers to reduce idle vibration and driving noise in the phase of preceding development. Thus, the issue of noise generation is drawing keen attention from production of prototype car through mass-production development. J. D. Power has surveyed the levels of customer satisfaction with all vehicles sold in the U.S. market and released the Initial Quality Study (IQS) index. As a growing number of emotional quality-related items are added to the IQS evaluation index, it is necessary to secure a sufficiently high quality level of low-frequency speaker sound against rattle noise. It is required to make a preceding review on the package tray panel, which is located at the bottom of the rear glass where the woofer speakers of a passenger sedan are installed, the door module panel in which the door speakers are built.

Generally, the HVAC system of a vehicle is composed of Blower unit assembly and Heater unit assembly, and is located on the driver’s side of the dash panel. However, electric vehicles have far fewer parts than conventional internal combustion engine vehicles, so electric vehicles have large space in the engine room. This allows HVAC, which occupies large volume in the interior side, to be pushed in the direction of the engine room altogether, or by placing a part inside the engine room to make a slim cockpit and expand the interior space. However, this new structure, called the Split HVAC System, is mounted through the dash, allowing noise to pass through relatively easily. Since this adversely affects the NVH of an electric vehicle, it needs to be developed in terms of noise transmission. Therefore, in this paper, a study was conducted to predict the sound transmission loss of Split HVAC through an analytical method.

The high-frequency whining noise produced by motors in modern electric vehicles causes a significant issue, leading to annoyance among passengers. This noise becomes even more noticeable due to the quiet nature of electric vehicles, which lack other noises to mask the high-frequency whining noise. To improve the noise caused by motors, it is essential to optimize various motor design parameters. However, this task requires expert knowledge and a considerable time investment. In this study, we explored the application of artificial intelligence to optimize the NVH performance of motors during the design phase. Firstly, we selected and modeled three benchmark motor types using Motor-CAD. Machine learning models were trained using Design of Experiment methods to simulate batch runs of Motor-CAD inputs and outputs.

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.

This paper presents the novel active vibration control (AVC) system that controls vehicle body vibration to reduce the structural borne road noise. As a result of vehicle noise testing in an electric vehicle, the predominant frequency of vehicle body vibration that worsens interior noise is in the range of 150-250Hz. Such vibration in that frequency range, commonly masked in engine vibrations, are hard to neglect for electric vehicles. The vibration source of that frequency is the resonance of tire cavity mode. Resonator or absorption material has been applied inside the tire for the control of cavity noise as a passive method. They require an increment of weight and cost. Therefore, a novel method is necessary. The vibration amplified by resonance of cavity mode is transferred to the vehicle body throughout the suspension system. To reduce the vibration, AVC system is applied to the suspension mount.

Even if an optimal design is produced in the mid-to-late stages of development, when the maturity of development is increasing, it is already difficult to accept the proposal between the organizations and functions. In case the optimal proposal is made with a small amount of information in the preceding stage, it will be helpful for mutual decision-making. In addition, if all members have a system and development environment that enables access and utilization of necessary data in a timely manner, it is possible to produce quick results through collaboration. To implement such a system and development environment, “digital modeling" of tangible and intangible assets will be essential and to implement an "integrated IT environment" that can access and utilize digital models. Until now, Hyundai Motor Company has not yet fully established a digital development environment that all researchers can simultaneously utilize during the concept development stage.

In this study, a co-operative regenerative braking control algorithm was developed for an electric vehicle (EV) equipped with an electronic wedge brake (EWB) for its front wheels and an electronic mechanical brake (EMB) for its rear wheels. The co-operative regenerative braking control algorithm was designed considering the road friction characteristic to increase the recuperation energy while avoiding wheel lock. A powertrain model of an EV composed of a motor, and batteries and a MATLAB model of the control algorithm were also developed. They were linked to the CarSim model of the vehicle under study to develop an EV simulator. The EMB and EWB were modeled with an actuator, screw, and wedge to develop an EMB and EWB simulator. A co-simulator for an EV equipped with an EWB for the front wheels and an EMB for the rear wheels was fabricated, composed of the EV and the EMB and EWB simulator.

In recent years, the automobile industry has been making efforts to develop vehicles that satisfy customers' emotions rather than malfunctions. The Vehicle Dependability Study(VDS) has been strengthened emotion items since the introduction of the new evaluation system VDS3 from 2015. The ratio of emotion items increased from 11% to 25%. In order to clarify the problem and cause of emotion items, we analyzed verbatim which is the customers' complaint data provided by J.D power every year, but it was difficult to extract customers' intention because the number of verbatim is small and expressed in terms of customer’s term rather than engineer’s term. To solve the problem, we are additionally colleting big data such as internet, warranty, online survey. Since the amount of data is very large, we developed textmining techniques such as dictionary, topic, Support Vector Machine(SVM), n-gram to improve process.

A battery pack case of an electric vehicle was developed with a fibrous thermoplastic composite material. Due to cost effectiveness, long-fiber-reinforced thermoplastics by direct process (D-LFT) were adopted. PA6 (Polyamide 6)-based composites were processed using a D-LFT pilot machine at the temperature range between 250° and 290°. Glass and carbon fibers were added in the matrix varying the mixture ratio of the fibers while keeping the weight fraction 40%. The increase of carbon fibers in the mixture increased tensile modulus and strength, however, decreased Izod impacts strength. The fatigue life of developed composites was evaluated by fatigue tests in tension, which were over one million cycles at the maximum fatigue loading less than 60% of the composite strength. Associated with fiber orientation, anisotropic mechanical behavior was investigated in terms of flexural properties and mold shrinkage.

In electric-powertrains, noise and vibration can be generated by components such as gears and motors. Often a noise phenomenon known as rumble or droning noise can occur due to low shaft order excitation at the spline. In this study, we identified the excitation source for spline induced rumble noise and developed a novel analysis method. First, a detailed spline model, believed to be the key factor for rumble noise, has been developed and verified by comparison with Finite Element Method(FEM) analysis. In order to identify an excitation source, a typical electric-powertrain assembly model including the developed spline model was constructed and simulated. Results according to changes of key factors including spline pitch errors and shaft alignment errors were analyzed. Spline radial force has been identified as an excitation source of spline induced rumble noise. This was verified through comparison with the forced vibration analysis result and time domain analysis result.

Recently, automobile manufacturers are interested in the development of battery electric vehicle (BEV) having a longer mileage to satisfy customer needs. The BEV with high efficiency depends on the temperature of the electric components. Hence it is important to study the effect of the cooling system in electric vehicle in order to optimize efficiency and performance. In this study, we present a 1-D vehicle thermal management (VTM) simulation model. The individual vehicle subsystems were modeled including cooling, power electric (PE), mechanical, and control components. Each component was integrated into a single VTM model and it would be used to calculate energy transfer among electrical, thermal, and mechanical energy. As a result, this simulation model predicts a plenty of information including the state of each component such as temperature, energy consumption, and operating point about electric vehicle depending on driving cycles and environmental conditions.

A new heat-resistant cast iron alloy has been developed for the exhaust manifolds of new passenger-car diesel engines. This development occurred because operating demands on exhaust manifolds have increased significantly over the past decade. These demands are due to higher exhaust gas temperatures resulting from tighter emission requirements, improved fuel efficiencies, and designs for higher specific engine power. These factors have led to much higher elevated temperature strength and oxidation resistance requirements on exhaust manifold alloys. Additionally, thermal fatigue that occurs directly as a result of thermal expansions and mechanical constraint has become an increasingly important issue. The research detailed in this paper focused on the optimization of the chemical composition of a Si-Mo ductile iron to improve the mechanical and physical properties for use in an engine exhaust manifold.

Passenger fatigue during long distance driving is greatly influenced by the comfort performance of the seat. Seat comfort performance is determined by the appropriate contour of the seat and the appropriate pad with sufficient thickness. The height of vehicle has been lowered to enhance car styling, and battery for electric vehicle applied to the underbody of the vehicle, reducing the package space of the seat in the vehicle. These external factors eventually lead to a reduced pad thickness of the seat cushion and compromise one of the important components in the seat cushion compartment, creating an uncomfortable cushioning problem when driving long distances. To improve the cushion composition of the seat within a limited package, air bladders are applied to the underside of the cushion pad. In addition, the function to support the buttocks using the air bladders of the lower cushion, similar to lumbar support for the back, was implemented to improve cushion comfort performance.

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.

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.

Reducing the emitted noise from vehicles is a primary issue for automotive OEMs due to the constant evolution of the noise regulations. In the context of electric powertrains, virtual prototyping has proven to be a cost-efficient alternative to the build-test process, especially in early design stage and/or if optimization is targeted. Due to the multiphysics nature of the model, the full simulation chain involves multiple components, each having its own specific modelling attributes. The difficulty then resides in the parts assembly, solving issues like mesh-to-mesh projections, time to frequency-domain transformation, 2d-axisymmetric to 3d mapping, data formatting and management, unit and local coordinate systems… This paper presents an environment that allows for the prediction and analysis of the noise radiated by electric automotive powertrains. The stator-rotor electro-magnetic behavior is represented by time-dependent forces applied on stator teeth.

Engine off control is conducted on parallel hybrid vehicles in order to reduce fuel consumption. It is efficient in terms of fuel economy, however, noise and vibration is generated on engine cranking and transferred through engine mount on every mode transition from EV to HEV. Engine crank position control has been studied in this paper in order to reduce vibration generated when next cranking starts. System modeling of an architecture composed of an engine, P1 and P2 motors has been conducted. According to the prior studies, there exists correlation between crank vibration level and the crank angle. Thus a method to locate pistons on a specific crank angle which results in a local minimum of vibration magnitude could be considered. The P1 motor facilitates this crank position control when engine turns off, for its location directly mounted on a crankshaft allows the system model to obtain more precise crank position estimation and improved linearity in torque control as well.