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As electric vehicles become more widespread, such vehicles may be subject to “range anxiety” due to the risk of discharging during driving or the discharging when left unused for a long period. Accordingly, a vehicle equipped with a mobile charger that can provide a charge in an emergency. The vehicle with the mobile charger is usually composed of a large capacity battery, a power converter in a small truck. However, the large capacity battery and the power converter are disadvantageous in that they are large in size and expensive and should be produced as a special vehicle. In this paper, we propose a method to solve the problem using an internal EV system without requiring an additional power generation, battery and a charging-and-discharging device. The method is a novel Vehicle-to-Vehicle (V2V) fast charging control system utilizing motor and inverter in EV.

In case of all gasoline vehicles such as the passenger vehicle, heavy duty truck and light duty truck etc., a fuel pump is located inside the fuel tank and transfers the fuel to an engine for stable driving, however, engine stall can be occurred by low pressure fuel pump. The boiling temperature of gasoline fuel is very low, the initial boiling point is around 40°C so fuel can boil easily while driving and end boiling point is around 190°C. It boils sequentially depending on the temperature. It becomes the criteria to determine the amount of vapor released inside the fuel tank at high temperature. The main cause of engine stall at high temperature is rapid fuel boiling by increasing fuel temperature. This causes a lot of vapor. Such vapor flows into the fuel pump which leading to decrease the pump load and the current consumption of the fuel pump continuously. This ultimately results in engine stall.

This paper suggests disturbance observer which improves performance of speed limit assist control. The nonlinear disturbance observer was designed so that disturbance caused by parameter and load uncertainties is able to be estimated exponentially. With the contribution of the observer, feed-forward and integral controllers can be omitted while improving steady-state error elimination and overshoot reduction. The acceleration observer is also designed to reduce the effect of wheel slip and changing slope. The performance of the controllers has been verified not only on flat roads, but also on wave road and rapidly changing ramps.

This paper presents an energy-optimal deceleration planning system (EDPS) to maximize regenerative energy for electrified vehicles on deceleration events perceived by map and navigation information, machine vision and connected communication. The optimization range for EDPS is restricted within an upcoming deceleration event rather than the entire routes while in real time considering preceding vehicles. A practical force balance relationship based on an electrified powertrain is explicitly utilized for building a cost function of the associated optimal control problem. The optimal inputs are parameterized on each computation node from a set of available deceleration profiles resulting from a deceleration time model which are configured by real-world test drivings.

An integrated starter and generator (ISG) is a type of electric machine which is mechanically connected to an internal combustion engine (ICE). The ISG is intended to conduct important roles in the hybrid electric vehicle (HEV) such as engine start and stop. Since the HEV has frequent electric vehicle (EV)/HEV mode transition, rapid engine cranking and vibration-free engine stop controls are necessary. In the case of the engine stop, the ISG provides the negative torque output to the ICE which can rapidly escape from its resonance speed. However, the ISG torque is determined by engineering intuition, the amount of energy recovery is hardly considered. Dynamic programming (DP) is an effective solution to find optimal ISG control strategy to maximize energy recovery during engine stop transition. Even though DP is an offline algorithm, the result can be used as a reference to evaluate and improve an existing on-line algorithm.

This research was to model a 6×4 tractor-trailer rig using TruckSim and simulate severe braking maneuvers with hardware in the loop and software in the loop simulations. For the hardware in the loop simulation (HIL), the tractor model was integrated with a 4s4m anti-lock braking system (ABS) and straight line braking tests were conducted. In developing the model, over 100 vehicle parameters were acquired from a real production tractor and entered into TruckSim. For the HIL simulation, the hardware consisted of a 4s4m ABS braking system with six brake chambers, four modulators, a treadle and an electronic control unit (ECU). A dSPACE simulator was used as the “interface” between the TruckSim computer model and the hardware.

Numerical durability analysis is the only approach that can be used to assess the durability of vehicles in early stages of development. In these stages, where there are no physical prototypes available, the road wheel forces (or spindle forces) for durability testing on Belgian PG (Proving Ground) must be predicted by VPG (Virtual Proving Ground) or derived from the measured forces of predecessor vehicles. In addition, the tuning parts and geometry are not fixed at these stages. This results in the variation of spindle forces during the development stages. Therefore, it is not reasonable to choose the forces predicted at a specific tuning condition as standard forces. It is more reasonable to determine the standard forces stochastically using the DB of the measured forces of predecessor vehicles. The spindle forces measured or predicted on Belgian PG are typically stationary random.

This paper presents an adaptation method of equivalent factor in equivalent consumption minimization strategy (ECMS) of fuel cell hybrid electric vehicle (FCHEV) using hilly road information. Instantaneous optimization approach such as ECMS is one of real-time controllers. Furthermore, it is widely accepted that ECMS achieves near-optimum results with the selection of the appropriate equivalent factor. However, a lack of hilly road information no longer guarantees near-optimum results as well as charge-sustaining of ECMS under hilly road conditions. In this paper, first, an optimal control problem is formulated to derive ECMS analytical solution based on simplified models. Then, we proposed updating method of equivalent factor based on sensitivity analysis. The proposed method tries to mimic the globally optimal equivalent factor trajectory extracted from dynamic programming solutions.

It is common knowledge that body structure is an important factor of road noise performance. Thus, a high stiffness of body system is required, and determining their optimized stiffness and structure is necessary. Therefore, a method for improving body stiffness and validating the relationship between stiffness and road noise through CAE and experimental trials was tested. Furthermore, a guideline for optimizing body structure for road noise performance was suggested.

This work studied the control technique for the engine clutch engagement at launch for the TMED parallel HEV for the improved drivability and dynamic performance. Analysis are done on the speed synchronization of the clutch plates, the speed control using the starter motor (ISG), and the fluid pressure control for the clutch. Possible external factors such as changes in the friction coefficient of transmission fluid, temperature variation, auxiliary power and pressure losses are identified and their effects on the targeted dynamic performance are examined. The targeted system performance was achieved with a learning control technique using fluid pressure as the only control input. This involves the compensation for the effect of external factors on the fluid pressure profile and this effect is memorized for the subsequent slip-launch application.

The efforts to improve automatic transmission (AT) efficiency for vehicle fuel economy are constantly continuing. In an AT the oil pump is the largest power loss factor. Therefore the effect on fuel economy is very high. The AT oil pump system has structural contradictions (high pressure × high flow), and the efforts to improve these areas are concentrated. In this paper, a two oil pumping system was designed to improve the efficiency and performance of a 6 speed AT installed in a Hybrid Electric Vehicle (HEV) [1], and the improvement was confirmed by a prototype experiment. As a result of the experiment, two pumping system was shown to improve vehicle fuel economy while reducing noise and oil pressure vibration.

Development of eco-friendly vehicles have risen in importance due to fossil fuel depletion and the strengthened globalized emission control regulatory requirements. A lot of automotive companies have already developed and launched various types of eco-friendly vehicles which include hybrid vehicles (HEVs) or electric vehicles (EVs) to reduce fuel consumption. To maximize fuel economy Hyundai-Kia Motor Company has introduced eco-friendly vehicles which have downsized or eliminated vibration damping components such as a torque converter. Comparing with Internal Combustion Engine(ICE) powered vehicles, one issue of the electric motor propulsion system with minimized vibration damping components is NVH (Noise, Vibration and Harshness). The NVH problem is caused by output torque fluctuation of the motor system, resulting in the degradation of ride comfort and drivability.

This paper proposes an effective nonlinear bicycle model including longitudinal, lateral, and yaw motions of a vehicle. This bicycle model uses a simplified piece-wise linear tire model and tire force tuning algorithm to produce closely matching vehicle trajectory compared to real vehicle for wide vehicle operation ranges. A simplified piece-wise tire model that well represents nonlinear tire forces was developed. The key parameters of this model can be chosen from measured tire forces. For the effects of dynamic load transfer due to sharp vehicle maneuvers, a tire force tuning algorithm that dynamically adjusts tire forces of the bicycle model based on measured vehicle lateral acceleration is proposed. Responses of the proposed bicycle model have been compared with commercial vehicle dynamics model (CarSim) through simulation in various vehicle maneuvers (ramp steer, sine-with-dwell).

The worldwide automotive industry is currently preparing for a market introduction of hydrogen-fueled powertrains. These powertrains in fuel cell electric vehicles (FCEVs) offer many advantages: high efficiency, zero tailpipe emissions, reduced greenhouse gas footprint, and use of domestic and renewable energy sources. To realize these benefits, hydrogen vehicles must be competitive with conventional vehicles with regards to fueling time and vehicle range. A key to maximizing the vehicle's driving range is to ensure that the fueling process achieves a complete fill to the rated Compressed Hydrogen Storage System (CHSS) capacity. An optimal process will safely transfer the maximum amount of hydrogen to the vehicle in the shortest amount of time, while staying within the prescribed pressure, temperature, and density limits. The SAE J2601 light duty vehicle fueling standard has been developed to meet these performance objectives under all practical conditions.

Currently, the interest in accelerated reliability testing (ART) of electric vehicles parts has been increasing. In particular, an electric motor and battery are vital components of battery powered electric vehicles. The electric motor has two major roles, to discharge or charge battery when it is driven or braking. For analyzing the exact behavior mechanism of electric motor and predicting lithium-ion battery cell degradation, new accelerated reliability testing technology is required. This paper describes the results of research and development in new approach to reliability testing for electric vehicles. The methodology to measure a precise motor output torque of the rotating rotor using telemetry system was provided. The electric energy quantities as well as the used quantities of the electric power were also analyzed. The results of research and development in new approach to reliability testing for electric vehicles were systematized and reflected in development.

Fuel cell vehicle is loaded with translating equipment, which converts chemical energy to electrical energy. The equipment has maximum power efficiency at a specific temperature when several operating conditions are met. To control the coolant temperature, the existing system uses a wax-type thermostat, which operates as the wax elements contracts and expands. However, there are several problems with the wax-type thermostat; it is impossible to measure real-time temperature and high pressure drop. To mitigate these problems, we developed a DC motor-driven 3-way valve that can control real-time temperature and low pressure drop. Application of the 3-way valve will improve fuel cell vehicle power and fuel efficiency.

Recently, in accordance with the increased interest of consumer in fuel efficiency due to the phenomenon of high oil price, complaints against actual fuel efficiency in the road in comparison with the certified fuel efficiency have been raised frequently. Especially in case of the hybrid vehicle which is highly popular for the reason of its high fuel efficiency compared with that of existing gasoline car, deviation in the fuel efficiency will be higher compared with that of gasoline car in accordance with the driving mode (downtown/highway), driver's driving style (wild/mild) and external environmental condition (gradient/temperature/altitude). To solve them, this paper developed a method so that the SOC (State Of Charge), EV/HEV mode transition point can be controlled variably in accordance with the driving mode, driver's driving style and external environmental condition by making the most of characteristics of hybrid.

Wide attention to fuel cell electric vehicles (FCEVs) comes from two huge issues currently the world is facing with: the concern of the petroleum reserves depletion due to consequent oil dependence and the earth global warming due in some extent to vehicle emissions. In this background, Hyundai, along with its sister company Kia, has been building the FCEVs and operating their test fleet with several tens of units at home and abroad. Since 2004, 32 passenger vehicles have been offered for the Department of Energy's controlled hydrogen fleet and infrastructure demonstration and validation project in the U.S. In the meantime, from 2006, 30 passenger vehicles as well as four buses, featuring the in-house developed fuel cell stack and its associated components, are currently under the domestic operation for the FCEV learning demonstration led by the Ministry of Knowledge and Economy.

Due to aging of a battery over lifetime, the rated power and nominal energy capacity will be reduced compared with the initial rated power and capacity. These result in influences on the vehicle driving performance and fuel economy. To monitor and diagnose the aging of the battery, in this paper, the method of predicting the available rated power and energy capacity of Li-ion battery under in-vehicle condition is proposed. Under constant power test, available power is calculated from the estimated parameters using recursive least square method. Further, available energy capacity is evaluated through SOH(cn) defined by the ratio of initial state-of-charge (SOC) variation to present SOC (\GdSOC ⁿ /ΔSOC ⁿ ) variation under arbitrary in-vehicle driving cycles. To verify the proposed method, experiments for aging Li-ion battery are performed in hybrid electric vehicle.

Supervisory control strategy of a hybrid electric vehicle (HEV) provides target powers and operating points of an internal combustion engine and an electric motor. To promise efficient driving of the HEV, it is needed to find the proper values of control parameters which are used in the strategy. However, it is very difficult to find the optimal values of the parameters by doing experimental tests, since there are plural parameters which have dependent relationship between each other. Furthermore variation of the test results makes it difficult to extract the effect of a specific parameter change. In this study, a model based parameter optimization method is introduced. A vehicle simulation model having the most of dynamics related to fuel consumption was developed and validated with various experimental data from real vehicles. And then, the supervisory control logic including the control parameters was connected to the vehicle model.