Driver curve speed model and its application to ACC speed control in curved roads

A speed control algorithm for an ACC (Adaptive Cruise Control) system for curved roads is proposed based on driver behavior characteristics. As the foundation of this research, a driver speed model for curved roads is developed using a series of experimental data regarding driver behavior. To adapt the model to each driver’s individual curve speed behavior, the coefficients of the model are identified in real time from the data sequences collected during drivers’ manual operation stage by a self-learning algorithm based on a Recursive Least-Square (RLS) method with a forgetting factor. Using this algorithm, the parameters of the driver model can be identified from the data collected in the manual operation phase, and the identification results are applied during the ACC automatic control phase. Based on the developed model, the ACC speed control algorithm is modified to provide each individual driver with a customized speed profile for the scenario of a curved road with no car ahead. Tests verify the applicability of the modified system.     

Cycle-simulation turbulence modelling of IC engines

Numerical simulations of IC engines are of high interest for automotive engineers worldwide. The simulation models should be as fast as possible, low-computational effort and predictive tool. The correct prediction of turbulence level inside the combustion chamber of spark ignition engines is the most important factor influencing to the engine working cycle. This paper presents a development of the k-ε turbulence model applied to the commercial cycle-simulation software with the high emphasis on the intake part. The validation was performed on two engine geometries with the variation of engine speed and load comparing the cycle-simulation results of the turbulent kinetic energy and in-cylinder temperature with 3-D CFD results. In order to apply the cycle-simulation turbulence model for the simulation of entire engine map, the parameterization model of turbulence constants was proposed. The parameterized turbulence model was optimized using NLPQL optimization algorithm where the single set of turbulence model parameters for each engine was found. A good agreement of the turbulent kinetic energy during the expansion was achieved when the turbulence affects the flame front propagation and combustion rate as well.     

Application of a modified thermostatic control strategy to parallel mild HEV for improving fuel economy in urban driving conditions

A modified thermostatic control strategy is applied to the powertrain control of a parallel mild hybrid electric vehicle (HEV) to improve fuel economy. This strategy can improve the fuel economy of a parallel mild HEV by operating internal combustion engine (ICE) in a high-efficiency region. Thus, in this study, experiments of a parallel mild HEV were conducted to analyze the characteristics of the hybrid electric powertrain and a numerical model is developed for the vehicle. Based on the results, the thermostatic control strategy was modified and applied to the vehicle model. Also, battery protection logic by using electrochemical battery model is applied because the active usage of battery by thermostatic control strategy can damage the battery. The simulation results of the vehicle under urban driving conditions show that the thermostatic control strategy can improve the vehicle’s fuel economy by 3.7 % compared with that of the conventional strategy. The results also suggest that the trade-off between the fuel economy improvement by efficient ICE operation and the battery life reduction by active battery usage should be carefully investigated when a thermostatic control strategy is applied to a parallel mild HEV.     

Aerodynamic design optimization of rear body shapes of a sedan for drag reduction

This study proposes an aerodynamically optimized outer shape of a sedan by using an Artificial Neural Network (ANN), which focused on modifying the rear body shapes of the sedan. To determine the optimization variables, the unsteady flow field around the sedan driving at very fast speeds was analyzed by CFD simulation, and fluctuations of the drag coefficient (C _D ) and pressure around the car were calculated. After consideration of the baseline result of CFD, 6 local parts from the end of the sedan were chosen as the design variables for optimization. Moreover, an ANN approximation model was established with 64 experimental points generated by the D-optimal methodology. As a result, an aerodynamically optimized shape for the rear end of the sedan in which the aerodynamic performance is improved by about 5.64% when compared to the baseline vehicle is proposed. Finally, it is expected that within the accepted range of shape modifications for a rear body, the aerodynamic performance of a sedan can be enhanced so that the fuel efficiency of the sedan can be improved. The YF SONATA, a sedan manufactured by Hyundai Motors Corporate, played a major role in this research as the baseline vehicle.     

Adaptive neuron control using an integrated error approach with application to active suspensions

This paper proposes a new neuron control strategy for an active vehicle suspension system, with the emphasis on the study of multivariable and uncertain suspension characteristics. The novelty of this strategy is in the use of integrated error, which consists of multiple output errors in the regulated plant. By combining the integrated error approach with the traditional neuron control (TNC), integrated error neuron control (IENC) is presented. It provides a direct control to the multiple outputs of the control plant simultaneously. Taking a quarter-car model as an example, the proposed control strategy is applied and comparative simulations are carried out with various vehicle parameters and road input conditions. Simulation results prove the effectiveness and robustness of the proposed IENC method. In addition, the newly proposed neuron scheme provides a simple yet efficient new possibility for the control of a class of uncertain multivariable systems similar to an active vehicle suspension.     

Comparison of HC species from diesel combustion modes and characterization of a heat-up doc formulation

This study summarizes engine speed and load effects on HC species emissions from premixed charge compression ignition (PCI) and conventional diesel combustion, and it evaluates diesel oxidation catalyst (DOC) formulations on a gas flow reactor for the purpose of diesel particulate filter regeneration or lean NO_x trap desulfation. HC emissions are sampled simultaneously by a Tedlar bag for light HC species and by a Tenax TA™ adsorption trap for semi-volatile HC species, and they are analyzed by gas chromatography with a flame ionization detector. The bulk temperature and residence time during combustion are key parameters that are important for understanding the effects of speed and load on engine-out HC emissions. The degree of post-flame oxidation is higher in PCI than in conventional combustion, and it is increased for PCI with a higher speed and load, as indicated by a lower fuel alkanes/THC ratio, a higher alkenes/fuel alkanes ratio, and a higher methane/THC ratio. Ethene and n-undecane are two representative HC species, and they are used as a surrogate mixture in the gas flow reactor to simulate PCI and conventional combustion with in-cylinder post fuel injection. Among the three DOC formulations tested, the catalyst with constituent precious metals of platinum and palladium (PtPd) showed the best light-off performance, followed by PtPd with an addition of cerium dioxide (PtPd+CeO₂), and platinum (Pt), regardless of exhaust compositions. Conventional combustion exhaust composition shows a lower light-off temperature than that of PCI, regardless of catalyst formulation.     

Fatigue design for plug/ring type gas welded joints of sts301l including welding residual stresses

This paper presents a fatigue design method for plug and ring type gas welded joints, which incorporates welding residual stress effects. A non-linear finite element analysis (FEA) was first performed to simulate the gas welding process. The numerically predicted residual stresses of the gas welds were then compared to experimental results measured using a hole drilling method. In order to evaluate the fatigue strength of the plug and ring type gas welded joints, a stress amplitude (σ _a ) _R taling the welding residual stress of the gas weld into account was introduced and is based on a modified Goodman equation incorporating the effect of the residual stress. Using the stress amplitude (σ _a ) _R , the ΔP-N _f relations obtained from fatigue tests for plug and ring type gas welded joints having various dimensions and shapes were systematically rearranged into (σ _a ) _R -N _f relations. It was found that the proposed stress amplitude (σ _a ) _R could provide a systematic and reasonable fatigue design criterion for the plug and ring type gas welded joints.     

Benthic sediment composition and nutrient cycling in an Intermittently Closed and Open Lake Lagoon

Surfical sediments within Corunna Lake, a moderate size Intermittently Closed and Open Lake Lagoon (ICOLL), were examined for solid phase nutrient concentrations (TN, TP, TOC,) and solute exchange rates between the sediment and water column (O₂, NO₃–N, NH₄–N, FRP, and N₂). The surfical sediments in Corunna Lake contained high concentrations of TN (5 mg/g dry mass), total phosphorus (0.6 mg/g dry mass), and TOC (~ 5% dry mass). The carbon stable isotope ratio (δ¹³C) and TOC:TN ratios (δ¹³C ~ ? 24, TOC:TN ~ 11–14) demonstrated that the composition of the organic matter in the sediment was a mixture derived primarily of degraded planktonic matter. The close association between TP and Fe concentrations highlighted the potential role Fe plays in mediating Filterable Reactive Phosphorus (FRP) concentrations in the water column of Corunna Lake. In situ benthic chamber incubations were used to measure benthic fluxes. Solute exchange rates between the sediment and water column in Corunna Lake were similar to other reported studies (O₂ = ? 469 to ? 1765 µmol m^? 2 h^? 1, NH₄–N = 0.1–63 µmol m^? 2 h^? 1, NO₂/NO₃–N = 0 µmol m^? 2 h^? 1, FRP = ? 4–1.6 µmol m^? 2 h^? 1and N₂ = 12–356 µmol m^? 2 h^? 1). As more carbon was deposited and mineralized the efficiency of the bacterial population to denitrify nitrogen in the sediment decreases. The linkage between land use and benthic biogeochemistry was also explored. A dairy farm exists in the middle catchment of Corunna Lake, and the receiving bay sediment consistently demonstrated the highest oxygen consumption rates in winter and spring (? 1408 µmol m^? 2 h^? 1 in winter, ? 1691 µmol m^? 2 h^? 1 in spring) and lowest denitrification efficiencies during summer (~ 3%). Nitrate/nitrite fluxes were not observed during any of the chamber incubations, with the concentrations of nitrate/nitrite being below detection limits (< 10 μg/L). Seasonal changes influenced the rates of solute exchange between the sediment and water column. Critical measures of solute exchange for NH₄–N and biogenic N₂ indicated that seasonal temperature changes play a significant role in mediating the reaction rates of sedimentary based biogeochemical processes. Measurable FRP fluxes were small but greater in the benthic sediments which received higher carbon inputs. Sediments have a high capacity to adsorb P which is released as sediment oxygen demand increases as a result of increases in labile carbon loads.     

A regional railroad network optimization model for coal transportation

A regional railroad network is presented to evaluate the system's response to increased coal traffic. An optimal, multimodal, coal-shipping pattern is developed for the study region to minimize total costs and to efficiently use the existing network. A two-stage, general model allocates resources among demands and then assigns flows to the network according to efficiency criteria. The model is sufficiently general to permit modification for specific needs, assumptions and data. Government agencies and industries can apply the model in resource allocation decisions and transportation policy analysis.