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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.

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.

This report explains the basic theory of designing the accelerating durability test road and the role of each factors contributing to the test road surface profile. Also this road is designed by considering the charactors of vehicle suspension system and conditions of driving. In test road, the factors affecting to the vehicle structural durability are correlation among surface shape of road profile, frequency of vehicle suspension system,distribution of axle twist angle and vibration of road profile height. Road PSD magnitude and frequency delay is used to control these factors relation.

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.

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 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.