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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.

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.

This paper proposes a new integrated chassis control (ICC) using a predictive model-based control (MPC) for optimal allocation of sub-chassis control systems where a predictive model has 6 Degree of Freedom (DoF) for rigid body dynamics. The 6 DoF predictive vehicle model consists of longitudinal, lateral, vertical, roll, pitch, and yaw motions while previous MPC research uses a 3 DoF maximally predictive model such as longitudinal, lateral and yaw motions. The sub-chassis control systems in this paper include four wheel individual braking torque control, four wheel individual driving torque control and four corner active suspension control. Intermediate control inputs for sub-chassis control systems are simplified as wheel slip ratio changes for driving and braking controls and vertical suspension force changes for an active suspension control.

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.

The series-parallel hybrid electric vehicle(HEV), which employs a planetary gear set to combine one internal combustion engine(ICE) and two electric motors(EMs), can take advantages of both series and parallel hybrid system. The efficient powertrain operating point of the system can be obtained by the instantaneous optimization of equivalent fuel consumption. However, heavy computational requirements and variable constraints of the optimization process make it difficult to build real-time control strategy. To overcome the difficulty, this study suggests the control strategy which divides the optimization process into 2 stages. In the first stage, a target of charge/discharge power is determined based on equivalent fuel consumption, then in the second stage, an engine operating point is determined taking power transfer efficiency into account.

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.

A vehicle drifts due to several reasons from its intended straight path even in the case of no steering input. The multibody dynamic analysis of vehicle drift during accelerating and braking are performed. This paper focuses on modeling and evaluating effects of suspension parameters, differential friction, engine mounting and C.G. location of the vehicle under multibody dynamic simulation environment. Asymmetry of geometry and compliance between left and right side is considered cause of drift. The sensitivities of the suspension parameters are presented for each driving condition. In case of acceleration, the interaction of differential friction and driveshaft stiffness and their influence on drift are also studied. For braking condition, suspension parameters such as initial toe variation of rear coupled torsion beam axle type suspension and kingpin inclination deviation of front suspension are studied including the braking force difference.

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.

Elastokinematic properties of the suspension system are one of major factors that improve ride and handling performances. Their properties have been quasi-statically determined using the in-door measurement device, such as the SPMD (Suspension Parameter Measurement Device). The elastokinematic properties in driving conditions, called dynamic compliance characteristics, are defined as the superposition of quasi-static properties, called static compliance characteristics. However, this superposition method has difficulties in predicting the suspension non-linearities under high lateral acceleration and transient behaviors. In this paper, dynamic compliance characteristics are directly determined through on-board measurements and transformation matrix. Their applications in validating ADAMS full vehicle model are discussed. Some experimental and simulation results about their unique properties and relationships with SPMD are presented.

In this paper, we deal with the automatic climate control for Recreational Vehicle (RV). The HVAC system used for RV was composed of front side and rear side. And, the HVAC system of front side differed from that of rear side in the characteristic of HVAC system. This system was economically optimized for automatic control over 2 separated zones. The development procedure of automatic climate controller was as follows. The first stage was to derive control equation from characteristic analysis of HVAC system and the structural characteristic of vehicle interior. In the second stage, the software (S/W) was designed and programmed to operate microprocessor which calculated previously mentioned equation. Finally, the hardware (H/W) design and building were performed to operate the HVAC system with the calculation results from microprocessor. The control performance of this automatic climate control algorithm and system was evaluated by experimental method.

This paper describes the development of THC reduction technologies compliant with SULEV regulations. Technologies embodied by the developmental work include improvement of fuel spay atomization, quick warm-up through coolant control shut off, and acceleration of fuel atomization for the fast rise of cylinder head temp inside the water jacket as well as the improvement of combustion state. The technologies likewise entail reduced HC while operating in lean A/F condition during engine warm-up with the cold lean-burn technology, individual cylinder A/F control for improvement of catalytic converting efficiency, aftertreatment such as thin-wall catalyst, HC absorber and EHC and etc., through vehicle application evaluation in cold start. We carried out an experimental as well as a practical study against SULEV regulations, and the feasibility of adopting these items in vehicle was likewise investigated.

In this paper we present the vision system used by the autonomous intelligent vehicle to sense the surrounding environment. With the B/W CCD camera, the system is able to detect the lane marking and to localize the vehicle''s position in real time and, thanks to an electric DC motor mounted on the steering column, it can autonomously steer the vehicle. We tested the system by implementing on EF SONATA (Hyundai Motor Co.) in the test field of laboratory and verified that the steering control drove the vehicle as smoothly as a human being along both straight and curve roads with maximum 100 k/h.

A throttle/brake control law for the intelligent cruise control (ICC) system has been proposed in this paper. The ICC system consists of a vehicle detection sensor, a controller and throttle/brake actuators. For the control of a throttle/brake system, we introduced a solenoid-valve-controlled electronic vacuum booster (EVB) and a step-motor-controlled throttle actuator. Nonlinear computer model for the electronic vacuum booster has been developed and the simulations were performed using a complete nonlinear vehicle model. The proposed control law in this paper consists of an algorithm that generates the desired acceleration/deceleration profile in an ICC situation, a throttle/brake switching logic and a throttle and brake control algorithm based on vehicle dynamics. The control performance has been investigated through computer simulations and experiments.

Hyundai Motor Company has developed hydrogen fuel cell vehicles (FCV) based on its SUV, Santa Fe. As the hydrogen fuel cell power plant runs at near ambient pressure, parasitic loss due to its operation is fully minimized and the noise level of the air supply subsystem is extremely low. The Santa Fe FCV has been built to feature roomy passenger space and cargo capacity identical to that of a standard, gasoline-powered Santa Fe, because of its compact fuel cell power plant. In addition, lightweight aluminum body-components help to keep a power-to-weight ratio similar to that of a conventional SUV. Hyundai Motor Company, as a full member of California Fuel Cell Partnership, is now operating the Santa Fe FCV's on real roads in California. In this paper, the configuration and performance test results of the Santa Fe FCV will be described.

A determination of the vehicle states and tire forces is critical to the stability of vehicle dynamic behavior and to designing automotive control systems. Researchers have studied estimation methods for the vehicle state vectors and tire forces. However, the accuracy of the estimation methods is closely related to the employed model. In this paper, tire lag dynamics is introduced in the model. Also application of estimation methods in order to improve the model accuracy is presented. The model is developed by using the global searching algorithm, a Genetic Algorithm, so that the model can be used in the nonlinear range. The extended Kalman filter and sliding mode observer theory are applied to estimate the vehicle state vectors and tire forces. The obtained results are compared with measurements and the outputs from the ADAMS full vehicle model. [15]

Hyundai has developed a Santa Fe fuel cell vehicle (FCV) in which methanol fuel processor is installed and integrated with PEM fuel cell system. Pure hydrogen is produced from the mixture of methanol and water by steam reforming followed by metal membrane purification and is then fed to fuel cell system to generate electrical energy. This system has the advantage of simplifying the integration of fuel cell subsystem and fuel processor subsystem. The operation of brassboard system has been carried out for performance evaluation and the development of fuel cell controller. And then the methanol reforming fuel cell system has been incorporated into electric drive train in the vehicle. AC induction motor is powered by the hybrid system using fuel cell and a nickel metal hydride battery as energy sources to improve the system efficiency and the acceleration response of the vehicle.

In this paper, four different levels of finite element models of a full vehicle were developed for ride comfort and brake judder dynamics analysis. The differences between the models are how elasticity of various vehicle components is modeled. The dynamic analysis was performed considering nonlinear effects for the different levels of models. The nonlinear effects were characterized by frequency and amplitude dependent stiffness and damping values of hydraulic engine mounting, suspension lower control arm bushing, tire, shock absorber, and suspension friction. At each modeling level, simulation results were compared to those of test measurements. The differences of the analysis results of these models and the effect of nonlinear characteristics were investigated. The developed models were applied to ride comfort and brake judder dynamics analysis.

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 paper presents the integrated chassis control(ICC) of four-wheel drive(4WD), electronic stability control(ESC), electronic control suspension(ECS), and active roll stabilizer(ARS) for limit handling. The ICC consists of three layers: 1) a supervisor determines target vehicle states; 2) upper level controller calculates generalized forces; 3) lower level controller, which is contributed in this paper, optimally allocates the generalized force to chassis modules. The lower level controller consists of two integrated parts, 1) longitudinal force control part (4WD/ESC) and 2) vertical force control part (ECS/ARS). The principal concept of both algorithms is optimally utilizing the capability of the each tire by monitoring tire saturation, with tire combined slip. By monitoring tire saturation, 4WD/ESC integrated system minimizes the sum of the tire saturation, and ECS/ARS integrated system minimizes the variance of the tire saturation.

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.