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In commercial vehicles, the exhaust brake assists the service brake to share the excess load and is used as an auxiliary brake to assist with the safety of the engine and the service brake on downhill slopes. To meet the customer's demand for auxiliary brakes, the specification of auxiliary brakes must be determined at the product proposal stage. In this study, performance design was conducted to derive exhaust brake specifications that fit the customer's requirements. For performance design, a system model was created and key design factors with high performance contribution were extracted. Optimal specifications were derived from parameter studies for key design factors. Additionally, performance analysis was performed with design tolerances using the performance design model. Performance was verified through actual vehicle evaluation and design specifications were confirmed.

After the COVID-19 pandemic, leisure activities and cultures have undergone significant transformations. Particularly, there has been an increased demand for outdoor camping. Consequently, the need for capabilities that allow vehicles to navigate not only paved roads but also unpaved and rugged terrains has arisen. In this study, we aim to address this demand by utilizing AI to introduce a 'Stuck Probability Estimation Algorithm' for vehicles on off-road. To estimate the 'Stuck Probability' of a vehicle, a mathematical model representing vehicle behavior is essential. The behavior of off-road driving vehicles can be characterized in two main aspects: firstly, the harshness of the terrain (how uneven and rugged it is), and secondly, the extent of wheel slip affecting the vehicle's traction.

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.

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.

The fuel economy of a vehicle can be improved by recuperating the kinetic energy when the vehicle is decelerated. However, if there is no electrical traction component, the recuperated energy can be used only by the other electrical systems of the vehicle. Thus, the fuel economy improvement can be maximized by balancing the recuperated energy and the consumed energy. Also, suitable alternator and battery management is required to maximize the fuel economy. This paper describes a design optimization process of the alternator and battery system equipped with recuperation control algorithms for a mid-sized sedan based on the fuel economy and system cost. A vehicle model using AVL Cruise is developed for cycle simulations and validated with experimental data. The validated model is used for the parametric study and design optimization of the alternator and battery systems with single and dual energy storage.

Hyundai Motor Company developed its second-generation fuel cell hybrid electric vehicle (FCEV) based on its small Tucson SUV. Compared to Hyundai's first generation fuel cell vehicle, the Santa Fe FCEV, the Tucson FCEV has an extended driving range plus cold weather starting capability. It incorporates numerous technical advances including a fuel cell that operates at sub-zero temperatures and a new high voltage lithium ion polymer battery. Using both a fuel cell and a high voltage battery as sources for driving energy, the Tucson hybrid system provides optimum driving conditions, which ensures high tank to wheel efficiency. The Tucson FCEV's power plant has been located in the front - under the front hood - unlike its predecessor Santa Fe FCEV, which featured an under-floor installation. More importantly, Tucson FCEV's driving range has been extended to 300km thanks to its 152-liter hydrogen storage tanks.

A semi-empirical index to evaluate the noise propensity of brake friction materials is introduced. The noise propensity index (NPI) is based on the ratio of surface and matrix stiffness of the friction material, fraction of high-pressure contact plateaus on the sliding surface, and standard deviation of the surface stiffness of the friction material that affect the amplitude and frequency of the stick-slip oscillation. The correlation between noise occurrence and NPI was examined using various brake linings for commercial vehicles. The results obtained from reduced-scale noise dynamometer and vehicle tests indicated that NPI is well correlated with noise propensity. The analysis of the stick-slip profiles also indicated that the surface property affects the amplitude of friction oscillation, while the mechanical property of the friction material influences the propagation of friction oscillation after the onset of vibration.

One of the ways to improve the fuel efficiency of the HEV (Hybrid and Electric Vehicles) is to optimize automotive electric system. In order to achieve this, the LDC (Low voltage DC-DC Converter) variable voltage was controlled. Using the ADAS (Advanced Driver Assistance System) map, the charge-discharge behaviors of 12V lead-acid battery was predicted during driving so that, the battery could be charged efficiently. In this study, the feedback control system for 12V battery discharging was designed to compromise between the 12V battery SOC (State of Charge) and the driving conditions at different traffic points. In contrast to earlier approaches, this experimental result indicates that the LDC variable voltage control based on ADAS is able to reduce the LDC average output power by 17.1% therefore, increasing fuel efficiency and ensuring the durability of the 12V battery.

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.

The performance and marketability of eco-friendly vehicles highly depend on their high-voltage battery system. Lithium-ion pouch cells have advantages of high energy density and cost-effectiveness than other types of batteries. However, due to their low mechanical stability, their characteristics are strongly influenced by external conditions. Especially, external pressure on pouch cell is a crucial factor for the performance, life cycle, and structural safety of battery pack. Therefore, optimizing pressure level has been a critical consideration in designing battery pack structures for lithium-ion pouch cell. In this work, we developed an optimized structure of the battery module and pack to apply appropriate pressure on pouch cells. They also include a standardization strategy to meet the varied demand in capacity and power for automotive application.

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.

The electric power system of a modern vehicle has to supply enough electrical energy to numerous electrical and electronic systems. The electric power system of a vehicle consists of two major components: a generator and a battery. A detailed understanding of the characteristics of the electric power system, electrical load demands, and the driving environment such as road, season, and vehicle weight are required when the capacities of the generator and the battery are to be determined for a vehicle. In order to avoid the over/under design problem of the electric power system, an easy-to-use and inexpensive simulation program may be needed. In this study, a vehicle electric power simulator is developed. The simulator can be utilized to determine the optimized capacities of generators and batteries appropriately. To improve the flexibility and easy usage of the simulation program, the program is organized in modular structures, and is run on a PC.

To properly respond to demands to reduce national energy consumption and meet greenhouse gas emission targets based on environment policy, the Ministry of Trade, Industry, and Energy of Korea formed a research consortium consisting of government agencies and academic and research institutions to establish the first fuel efficiency standards for medium- and heavy-duty (MHD) commercial vehicles. The standards are expected to be introduced in 2017 as Phase 1 of the plan and will regulate trucks with a gross vehicle weight in excess of 3.5 tons and buses with a carrying capacity of more than 16 persons. Most MHD commercial vehicles are custom-made and manufactured in diversified small-quantity batch production systems for commercial or public use, resulting in difficulties in utilizing mandatory vehicle tests for fuel efficiency evaluations.

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.

Recently electric and electronic devices in vehicle have been rapidly increasing. Because the dynamic characteristics of these systems are too much complicated, it is getting very difficult to predict the change of electrical energy accurately. Especially, since the lead-acid battery has a fast aging process, managing the electrical energy in vehicle becomes more difficult. This paper shows the electrical energy simulator, which consists of a battery, an alternator and various electrical devices. In particular, proposed aging battery model was implemented using a finite element method (FEM) based on electrochemical approach. And the thermal characteristic of alternator is also focused on getting reliable performance. Finally, we validated the electrical energy simulator including this battery model on the actual conditions in vehicle.

Suspension system of vehicle is very important because it has an effect on ride comfort and safety. And the leaf spring is one of the major parts of commercial vehicle. By that reason it has to be designed to operate under severe condition to ensure enough endurance. But the traditional method for fatigue design needs repeated fatigue tests for each design according to its geometry, material, and operating condition. This means that a lot of time and money is needed for those tests. Thus, in this paper, a fatigue design method for leaf spring based on numerical analysis is proposed. At first, stress analysis is performed to get the stress under operation load or rig tests. And fatigue analysis is performed to get the fatigue life and to ensure the safety of leaf spring. Through this study, design parameters that play vital role in fatigue life of the leaf spring can be found out.

In the path following problem, a commercial vehicle has a delay of a hydraulic steering actuator and slow steering response accordingly. In addition, there are disturbances due to the harsh driving conditions of commercial vehicles. These disturbances may include uncertainties about actuator dynamic delay, modeling error and steering angle sensor offset. Designing a lateral controller with good performance that can overcome this problem is the key to successfully carrying out autonomous driving of commercial vehicles. Usually, it is difficult to consider disturbances with uncertainties in the geometric based control methods. Therefore, this paper proposed a lateral controller using feedback augmented disturbance observer for the commercial vehicle. First, a dynamics was modeled which can describe delay of the hydraulic actuator of the commercial vehicle. After that, a lateral controller was designed based on this dynamics model.

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.

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.

This paper proposes a speed controller using a disturbance observer to regulate the speed of a commercial vehicles, and presents vehicle test results to evaluate the performance of the proposed controller. Most ADAS (Advanced Driver Assistance System) and automated driving systems need to reliably regulate the vehicle's speed under any circumstances. A conventional PID controller is commonly used to control the vehicle speed, but performance of it varies depending on changes in external conditions. Commercial vehicles are even more susceptible to these changes than passenger cars and more difficult to obtain an accurate plant model. Considering these features, a speed controller using a disturbance observer is designed for commercial vehicles. The proposed controller treats changes in external conditions as disturbances. The modeling uncertainty is also treated as a disturbance.