Development of a biology inspired manufacturing system for machining transmission cases

Disruptions in automated manufacturing systems for machining automotive parts caused by system changes and disturbances reduce the productivity, and increase the downtime as well as the cost of products. To cope with these challenges, the paper presents a biology inspired manufacturing system (Bio-MS). The model of Bio-MS is inherited from the organization of the living systems in biology and nature such as ant colony, school of fish, bee’s foraging behaviors, and so on. In which, the resources of the manufacturing system are considered as biological organisms, which are autonomous entities so that the manufacturing system has the advanced characteristics inspired from biology such as self-adaptation, self-diagnosis, and self-healing. To realize the Bio-MS, the cognitive agent and swarm intelligence were proposed. The disturbances happening when machining the transmission cases at an automotive company in Korea were analyzed to classify them and to find out the corresponding management methods. Currently, the system utilization was too low due to the manual recovery, only 70–76 percent of total production time is used for manufacturing and the rest of the time is wasted in different disturbances. The Bio-MS with autonomous behaviors adapts efficiently to the changes of the manufacturing environment. It enables to increase the system utilization more than 80 percent.     

Dynamic sensor zeroing algorithm of 6D IMU mounted on ground vehicles

The main focus of this paper is to compensate the steady state offset error of the 6D IMU which provides the measurements that include the vehicle linear accelerations and angular rates of all three axes. Additionally, the sensor compensation algorithm exploits the wheel speed data and the steering angle information, since they are already available in most of the modern mass production vehicles. These inputs are combined with the inverse vehicle kinematics to estimate the steady state offset error of each sensor inputs as it is done in a disturbance observer, and the raw sensor measurements are compensated by the estimated offset errors. The stability of the error dynamics regarding the integrated signal processing system is verified, and finally, the performance of the system is tested via experiments based on a real production SUV.     

Robust design optimization of suspension system considering steering pull reduction

This paper presents robust design optimization method to reduce steering pull phenomenon. One of the biggest causes of steering pull phenomenon is tolerance of suspension system such as hard point, spring, damper and bush. Therefore, the relationship between suspension systems and steering pull phenomenon has as nonlinear characteristics. But, it can be very difficult to evaluate the analytical design sensitivity. Thus, it is impossible to directly apply a well-developed optimization algorithm based on gradient information. To avoid these difficulty, this study uses sequential approximation optimization process based on a meta-model. The robust design process has 28 random design variables with tolerance. For efficient design process, the sample variances for the design goals are approximated from meta-models. The proposed approach required only 62 evaluations until it converged. Optimal design reduced the drift by 80% and its deviation by 38.7%, respectively. This result proves that the suggested design method of suspension system is effective and useful.     

Nonlinear dynamic modeling of an electro-pneumatic pressure converter for VGT pneumatic actuator

This paper presents a detailed physical model of an electro-pneumatic system, used to control Variable Geometry Turbochargers (VGT). The VGT actuator system consists of two parts, a diaphragm based pneumatic actuator and a solenoid based Electro-pneumatic Pressure Converter (EPC). The proposed model copes with the pressure dynamics inside the pneumatic actuator, with special focus on the EPC. The dynamics of both parts have been modeled separately and combined into one model by parameterizing the effective flow area and the air mass flow through the pneumatic actuator. The variations in volume, temperature and air mass flow rate have been taken into account. The model so obtained serves mainly for studying the effect of actuator dynamics on the global engine system. For control purposes, the detailed model is simplified to reduce the calculation load. Both models are validated using experimental data obtained from an engine test bench.     

Objective evaluation of door-closing sound quality based on physiological acoustics

This paper presents a new method to objectively quantify the sound quality of doors closing in premium passenger cars. In previous works, psychoacoustic parameters have been used for objective quantification. However, these parameters do not agree well with subsequent subjective assessments. Therefore, the correlation between the psychoacoustic parameters and the subjective rating of door closing sounds in sampled cars is low, and it is not sufficient to use psychoacoustic parameters as an objective metric to quantify the quality of door-closing sounds. In this paper, a new method is proposed to objectively quantify the sound quality based on physiological acoustics and statistical signal processing. A gammatone filter is used as a pre-processing method in models of the auditory system and kurtosis, which is the fourth-order moment of the temporal signal and is used to extract quantitative information about the quality of door-closing sounds. The new metric obtained from the proposed method is highly correlated to subjective ratings and has been successfully applied to the quantification of door-closing sound quality.     

Gasoline multiple premixed compression ignition (MPCI): Controllable, high efficiency and clean combustion mode in direct injection engines

A novel combustion concept namely “multiple premixed compression ignition” (MPCI) in gasoline direct injection compression ignition (GDICI) regime is proposed. Its predominant feature is the first premixed and followed quasipremixed combustion processes in a sequence of “spray-combustion-spray-combustion”. The multiple-stage premixed combustion decouples the pressure rise with pollutants formation process, which means the pressure rise rate and emissions can be reduced simultaneously, while achieving a high thermal efficiency. The gasoline MPCI mode has been demonstrated in a research engine with a compression ratio of 18.5. Gasoline with the research octane number (RON) of 94.4 was tested under 1400 rpm, 0.6 MPa IMEP conditions, without EGR and intake boosting. A parameter study of common rail pressure and intake temperature was implemented to investigate their effects on the performance of MPCI mode. Compared to the single-stage diffusion combustion in traditional diesel engines, the gasoline MPCI mode achieves lower emissions of soot, NO, CO, as well as slightly higher indicated efficiency, with a penalty of higher THC emissions when the common rail pressure is larger than 80 MPa in this study. With intake temperature sweeping, the gasoline MPCI mode also has the foregoing advantages compared to the diesel under the same operating conditions.     

Cooling performance of 25 kW in-wheel motor for electric vehicles

The in-wheel motor used in electric vehicles was designed and constructed for an electric direct-drive traction system. It is difficult to connect cooling water piping to the in-wheel motor because the in-wheel motor is located within the wheel structure. In the air cooling structure for the in-wheel motor, an outer surface on the housing is provided with cooling grooves to increase the heat transfer area. In this study, we carried out the analysis on the fluid flow and thermal characteristics of the in-wheel motor for various motor speeds and heat generations. In order to resolve heat release, the analysis has been performed using conjugate heat transfer (conduction and convection). As a result, flow fields and temperature distribution inside the in-wheel motor were obtained for base speed condition (1250 rpm) and maximum speed condition (5000 rpm). The thermo-flow analysis of the in-wheel motor for vehicles was performed in consideration of ram air effect. Also, in order to improve cooling effect of the motor, we variously changed geometries of housing. Therefore, we confirmed the feasibility of the air cooling for the motors of 25 kW capacity with housing geometry having cooling grooves and investigated the cooling performance enhancement. We found that the cooling effect was most excellent, in case that cooling groove direction was same with air flow direction and arranged densely.     

Angular position error detection of variable reluctance resolver using simulation-based approach

The variable reluctance type resolver is widely used in an electric motor for hybrid electric vehicles as a rotor position sensor. The purpose of this paper is to present a simulation-based approach capable of determining a more accurate rotor shape of variable reluctance resolver in order to cut the time and cost of its development before testing a physical prototype. For the verification of the simulation-based approach to the position error detection of rotor, experiments for 8XVR resolver were conducted. Based on this approach, an optimal salient-pole rotor shape of 4X-VR resolver is proposed.     

Longer-term changes in mode choice decisions in Chennai: a comparison between cross-sectional and dynamic models

The rapid and continuing changes in travel and mobility needs in India over the last decade necessitates the development and use of dynamic models for travel demand forecasting rather than cross-sectional models. In this context, this paper investigates mode choice dynamics among workers in Chennai city, India over a period of five years (1999–2004). Dynamics in mode choice is captured at four levels: exogenous variable change, state-dependence, changes in users’ sensitivity to attributes, and unobserved error terms. The results show that the dynamic models provide a substantial improvement (of over 500 log-likelihood points and ρ² increases from 44% to 68%) over the cross-sectional model. The performance was compared using two illustrative policy scenarios with important methodological and practical implications. The results indicate that cross-sectional models tend to provide inflated estimates of potential improvement measures. Improving the Level of Service (LOS) alone will not produce the anticipated benefits to transit agencies, as it fails to overcome the persistent inertia captured in the state-dependence factors. The results and models have important applications in the context of growing motorization and congestion management in developing countries.

The Application of Linear Optimal Control Theory to the Design of Active Automotive Suspensions

Some linear stochastic control theory relevant to the design of active suspension systems subject to integrated or filtered white noise excitation is reviewed, and application of the theory to a particular problem is considered. The problem considered is the well known quarter car problem in which a control law which minimises a performance function representing passenger discomfort, suspension working space, and tyre load fluctuations is required. With full state feedback, the requirement for a formulation of the problem which leads to the system under consideration being observable and controllable is referred to, and it is shown how a well known coordinate transformation enables this requirement to be satisfied. With limited state (or output) feedback, problem formulations which will avoid potential numerical problems in deriving the optimal control are described. Example solutions are included in order to illustrate the methods.