Ford Motor Company

About: Ford Motor Company is a company organization based out in Dearborn, Michigan, United States. It is known for research contribution in the topics: Internal combustion engine & Signal. The organization has 36123 authors who have published 51450 publications receiving 855200 citations. The organization is also known as: Ford Motor & Ford Motor Corporation.

Impact of the heterogeneous hydrolysis of N2O5 on chemistry and nitrate aerosol formation in the lower troposphere under photosmog conditions

Abstract: [1] The impact of the heterogeneous hydrolysis of N2O5 on tropospheric gas phase and particle phase chemistry was investigated by performing model simulations with two comprehensive model systems and taking into account recent findings on the heterogeneous reaction probability of N2O5. Hereby, we focused on photosmog conditions in the lower troposphere. Chemistry box model runs were carried out neglecting transport and deposition processes. The heterogeneous hydrolysis of N2O5 leads to a decrease of ozone under low-NOx conditions and to a strong increase of ozone under high-NOx conditions. One-dimensional simulations were performed to take into account vertical mixing processes, deposition, and temporal changes of the emissions. The rate constant for the heterogeneous hydrolysis was determined depending on the simulated aerosol surface area density. A large impact of the heterogeneous hydrolysis on the nocturnal concentrations of N2O5, NO3, HNO3, and the surface area density and nitrate content of the aerosol is found. However, the effect of the hydrolysis of N2O5 on ozone decreases considerably compared to the box model simulations. Three-dimensional simulations for a typical summer smog situation for the southwestern part of Germany and on the European scale, which cover a variety of atmospheric and emission conditions, confirm these findings. The impact of heterogeneous hydrolysis on ozone is small, but it causes remarkable changes in the nocturnal concentrations of nitrogen-containing species and on aerosol properties such as surface area density and nitrate content.

Autonomous control in a dense vehicle environment

Abstract: A computer in a first vehicle is programmed to receive a first set of data from at least one sensor in the first vehicle and to receive a second set of data from at least one second vehicle. The second set of data is from at least one sensor in the at least one second vehicle. The computer is further programmed to use both the first set of data and the second set of data to identify at least one feature of a road being traversed by the first vehicle.

Psychiatric sequelae of low birth weight at 6 years of age

Abstract: The study examined the association between low birth weight (LBW) (≤2,500 g) and attention deficit hyperactivity disorder (ADHD) in two socioeconomically disparate populations. LBW and normal birth weight (NBW) children from the 1983 to 1985 newborn lists of an urban and a suburban hospital in Southeast Michigan were randomly selected. A total of 823 children, 473 LBW and 350 NBW, participated. Data were gathered in 1990 to 1992, when the children were 6 to 7 years of age. The National Institute of Mental Health Diagnostic Interview Schedule for children—Parent version (DISC-P) was used to elicit information on DSM-III-R diagnoses of simple phobia, overanxious, separation anxiety, oppositional defiant, and ADHD. Teachers' ratings of behavior problems were obtained. LBW was associated with ADHD but not with childhood anxiety disorders or oppositional defiant disorder. The association was stronger in the urban than in the suburban population. Data from teachers' ratings revealed an association between LBW and attention problems. The prognostic significance of the observed psychopathology at 6 years of age requires follow-up assessment as the children mature.

Derivation and Experimental Validation of a Power-Split Hybrid Electric Vehicle Model

Abstract: Hybrid electric vehicles (HEVs) have attracted a lot of attention due to environmental and efficiency reasons. Typically, an HEV combines two power trains, a conventional power source such as a gasoline engine, a diesel engine, or a fuel cell stack, and an electric drive system (involving a motor and a generator) to produce driving power with a potential of higher fuel economy than conventional vehicles. Furthermore, such vehicles do not require external charging and thus work within the existing fueling infrastructures. The power-split power train configuration of an HEV has the individual advantages of the series and parallel types of HEV power train configurations. A sophisticated control system, however, is required to manage the power-split HEV power trains. Designing such a control system requires a reasonably accurate HEV system plant model. Much research has been done for developing dynamic plant models for the series and parallel types, but a complete and validated dynamic model for the power-split HEV power train is still in its infancy. This paper presents a power-split power train HEV dynamic model capable of realistically replicating all the major steady-state and transient phenomena appearing under different driving conditions. A mathematical derivation and modeling representation of this plant model and its components is shown first. Next, the analysis, verification, and validation through computer simulation and comparison with the data actually measured in the test vehicle at the Ford Motor Company's test track is performed. The excellent agreements between the model and the experimental results demonstrate the fidelity and validity of the derived plant model. Since this plant model was built by integrating the subsystem models using a system-oriented approach with a hierarchical methodology, it is easy to change subsystem functionalities. The developed plant model is useful for analyzing and understanding the dominant dynamics of the power train system, the interaction between subsystems and components, and system transients due to the change of operational state and the influence of disturbances. This plant model can also be employed for the development of vehicle system controllers, evaluation of energy management strategies, issue resolution, and verification of coded algorithms, among many other purposes