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The BMW Group has introduced electric cars to the market with the MINI E already in 2009. The next step will be the launch of the BMW ActiveE in 2011, followed by the revolutionary Mega City Vehicle in 2013. The presentation will explain the BMW Group strategy for implementing sustainable mobility. A focus will be emobility, the use of carbon fiber and the holistic sustainability approach of BMW Group?s project i. Reference will be made to the research results of the MINI E projects in the US and in Europe. Presenter Andreas Klugescheid, BMW AG

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 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.

A new hydrogen fueling protocol named MC Formula Moto was developed for fuel cell motorcycles (FCM) with a smaller hydrogen storage capacity than those of light duty FC vehicles (FCV) currently covered in the SAE J2601 standard (over than 2kg storage). Building on the MC Formula based protocol from the 2016 SAE J2601 standard, numerous new techniques were developed and tested to accommodate the smaller storage capacity: an initial pressure estimation using the connection pulse, a fueling time counter which begins the main fueling time prior to the connection pulse, a pressure ramp rate fallback control, and other techniques. The MC Formula Moto fueling protocol has the potential to be implemented at current hydrogen stations intended for fueling of FCVs using protocols such as SAE J2601. This will allow FCMs to use the existing and rapidly growing hydrogen infrastructure, precluding the need for exclusive dispensers or stations.

The development of hydrogen-fueled vehicles has created the need for established fuel consumption testing methods. Until now the EPA has only accepted three methods of hydrogen fuel consumption testing, gravimetric, PVT (stabilized pressure, volume and temperature), and Coriolis mass flow; all of which necessitate physical measurements of the fuel supply [1]. BMW has developed an equation and subsequent testing methods to accurately and effectively determine hydrogen fuel consumption in light-duty vehicles using only exhaust emissions. Known as “Hydrogen-Balance”, the new equation requires no changes to EPA procedures and only slight modifications to most existing chassis dynamometers and CVS (Constant Volume Sampling) systems. The SAE 2008-01-1036, also written by BMW, explains the background as well as required equipment and changes to the CVS testing system. This paper takes hydrogen balance further by testing it against the three EPA established forms of fuel consumption.

The Hydrogen-Balance equation makes it possible to calculate the fuel economy or fuel consumption of hydrogen powered vehicles simply by analyzing exhaust emissions. While the benefits of such a method are apparent, it is important to discuss possible influencing factors that may decrease Hydrogen-Balance accuracy. Measuring vehicle exhaust emissions is done with a CVS (Constant Volume Sampling) system. While the CVS system has proven itself both robust and precise over the years, utilizing it for hydrogen applications requires extra caution to retain measurement accuracy. Consideration should be given to all testing equipment, as well as the vehicle being tested. Certain environmental factors may also play a role not just in Hydrogen-Balance accuracy, but as also in other low emission testing accuracy.

Today's automotive software integration is a static process. Hardware and software form a fixed package and thus hinder the integration of new electric and electronic features once the specification has been completed. Usually software components assigned to an ECU cannot be easily transferred to other devices after they have been deployed. The main reasons are high system configuration and integration complexity, although shifting functions from one to another ECU is a feature which is generally supported by AUTOSAR. The concept of a Virtual Functional Bus allows a strict separation between applications and infrastructure and avoids source code modifications. But still further tooling is needed to reconfigure the AUTOSAR Basic Software (BSW). Other challenges for AUTOSAR are mixed integrity, versioning and multi-core support. The upcoming BMW E/E-domain oriented architecture will require all these features to be scalable across all vehicle model ranges.

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.

Although hydrogen ICE engines have existed in one sort or another for many years, the testing of fuel consumption by way of exhaust emissions is not yet a proven method. The current consumption method for gasoline- and diesel-fueled vehicles is called the Carbon-Balance method, and it works by testing the vehicle exhaust for all carbon-containing components. Through conservation of mass, the carbon that comes out as exhaust must have gone in as fuel. Just like the Carbon-Balance method for gas and diesel engines, the new Hydrogen-Balance equation works on the principle that what goes into the engine must come out as exhaust components. This allows for fuel consumption measurements without direct contact with the fuel. This means increased accuracy and simplicity. This new method requires some modifications to the testing procedures and CVS (Constant Volume Sampling) system.

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.

The results of previous Life Cycle Assessments indicate the ecological dominance of the vehicle's use phase compared to its production and recycling phase. Particularly the so-called weight-induced fuel saving coefficients point out the great spectrum (0.15 to 1.0 l/(100 kg · 100 km)) that affects the total result of the LCA significantly. The objective of this article, therefore, is to derive a physical based, i.e. scientific chargeable and practical approved, concept to determine the significant parameters of a vehicle's use phase for the Life Cycle Inventory. It turns out that - besides the aerodynamic and rolling resistance parameters and the efficiencies of the power train - the vehicle's weight, the rear axle's transmission ratio and the driven velocity profile have an important influence on a vehicle's fuel consumption.

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.

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 study suggests new types of catalysts that show low hydrogen sulfide emission without scavenger such as NiO. Hydrogen sulfide can be reduced by changing the physicochemical properties of washcoat components. Synthesized gas activity tests were performed to investigate the effect of modified washcoat on hydrogen sulfide formation and catalytic activity. BET surface area tests, X- ray diffraction tests, and gas chromatography tests were also carried out to examine the characteristics of catalysts. Preparation methods for catalysts were focused on minimizing the adsorption of sulfur species on catalysts. The first approach is heat treatment of cerium oxide to reduce adsorption sites for sulfur compounds. But this leads to deterioration of CO and NOx conversion efficiencies. The second one is adding new types of promoters that increase thermal durability and dynamic oxygen storing function of cerium oxide.

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.

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.

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.

Flame Ionization Detectors (FID) can be used to detect organic hydrocarbons that occur in plastics, lacquers, adhesives, solvents and gasoline. These substances are ionized in the hydrogen flame of the FID. The ionization current that is produced depends on the amount of hydrocarbon in the sample. With the lowering of emissions limits, measuring instruments, including the FID, have to be able to detect very low values. For SULEV (Super-Ultra Low Emissions Vehicle) measurements the accuracy and also the general applicability of the CVS (Constant Volume Sampling) measuring technique are now questioned. Basic understanding is necessary to ask the right questions. One important issue is the science behind the measurement principle of the FID. And in this case especially the influence of contamination of the operating gases, cross sensitivity and data processing on the Limit of Detection (LOD).

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.