Component Sizing of Parallel Hybrid Electric Vehicle Using Optimal Search Algorithm

In designing a parallel hybrid electric vehicle, it is essential to select the optimal capacity of power sources and the optimal gear ratio of the torque coupler. The capacity of the power sources and the gear ratio of the torque coupler should be optimized simultaneously. However, since this process is excessively time-consuming, previous studies have selected the gear ratio of the torque coupler and then selected the capacity of power source. However, this approach cannot guarantee global optimization. In this paper, a feasible region is defined to satisfy the required performance of vehicle such as maximum speed, hill-climbing. and feasible points are selected inside the feasible region. In the conventional technique, the global optimal solution is obtained by simulating all feasible points. In the optimization technique, optimal points are simulated within the feasible region using several optimal search algorithms, such as the golden section search algorithm and the hillclimbing search algorithm. And using these algorithms, the number of simulations is reduced and the capacity of the power source and the gear ratio of the torque coupler are optimized simultaneously. Finally, the validity of the component sizing results is verified by comparing the global optimal solution obtained by applying the conventional technique with the solution obtained by applying the proposed optimization technique.     

Performance evaluation of slim low-risk-deployment dual-type passenger airbag system with dispersed inflation pressure

Motor vehicle passenger airbags have been proven to be effective for reducing the possibility of passenger injury during a crash. However, the inflation of the airbag sometimes causes serious injury when a passenger is positioned close to the airbag. The United States Federal Motor Vehicle Safety Standard (FMVSS) 208 requires the use of a low-riskdeployment (LRD) passenger airbag system. This paper proposes a newly developed airbag system comprising two slim airbags mounted on the instrument panel. A series of tests were conducted using the FMVSS 208 test procedures to demonstrate the effectiveness of the proposed system. It was found that the system not only satisfied the injury criteria of FMVSS 208, but was also effective for protecting passengers of all sizes.     

Active coolant control strategies in automotive engines

The coolant flow rate in conventional cooling systems in automotive engines is subject to the mechanical water pump speed, and high efficiency in terms of fuel economy and exhaust emission is not possible given this limitation. A new technology must be developed for engine cooling systems. The electronic water pump is used as a substitute for the mechanical water pump in new engine cooling systems. The new cooling system provides more flexible control of the coolant flow rate and engine temperature, which previously relied strongly on engine driving conditions such as load and speed. In this study, the feasibility of two new cooling strategies was investigated using a simulation model that was validated with temperatures measured in a diesel engine. Results revealed that active coolant control using an electronic water pump and valves substantially contributed to a reduction of coolant warm-up time during cold engine starts. Harmful emissions and fuel consumption are expected to decrease as a result of a reduction in warm-up time.     

Quantifying individuals’ trade-offs between privacy,liberty and security: The case of rail travel in UK

Public transport systems have been targets in several terrorist attacks, notably in recent years, resulting in tight security measures worldwide. However, individuals’ privacy and liberty often conflict with efforts towards safety and security, making it difficult to assess the implications of security measures balanced against the costs (e.g., citizens may be stopped, searched and asked to provide personal identification data to authorities without any particular reason). Henceforth, our research question asks, “to what extent would people sacrifice their right to privacy and liberty in exchange for potentially safer and more secure travel?” This paper uses a stated choice experiment to quantify individuals’ trade-offs between privacy and security within a real-life context, namely rail travel in the UK. Using a nationwide sample, the empirical analysis yields the importance of improvements in the security infrastructure and identifies areas of concern with regard to privacy and liberty controlling for travel related factors. Further, trade-offs across different security measures for rail travel are quantified in terms of individuals’ willingness-to-pay extra on top of the average ticket price.     

Design of ferrite magnet CFSM to improve speed response of EPS system

This paper deals with the speed response characteristic of the concentrated flux synchronous motor (CFSM) using ferrite magnets for the electric power steering (EPS) system. To analyze the response characteristic of the CFSM, an analytical method using the electromechanical undamped natural frequency and damping ratio based on the transfer function is proposed. By using the method, the speed response according to the variations of the shape of the permanent magnets (PMs) and rotor core is analyzed. It was analyzed under the conditions of the constant volume of the PMs as well as the constant diameter of the rotor. By using the proposed analysis method, the improved model is desgined based on the initial model fulfilling the required specifications. Finally, the torque and speed response characteristics of two motors are simulated through the finite element analysis (FEA) and MATLAB Simulink.     

Analysis of automotive disc brake squeal considering damping and design modifications for pads and a disc

The squeal noise occurring from the disc brakes of passenger cars has been analyzed by using the complex eigenvalue method numerically. The contact between a disc and two pads was analytically modeled as many linear springs and dampers in an effort to develop the improved equation of motion derived on the basis of Lagrange’s equation and the assumed mode method. The finite element modal analysis results for disc brake components constitute an eigenvalue matrix in the analytical equation of motion. The complex eigenvalue analyses based on the equations of motion are able to examine the dynamic instability of a brake system, which is an onset of squeal, by considering the disc rotational effect. Numerical analyses showed that the modes unstable in an undamped analysis became stable in a damped case, which illustrates the important effect of damping on the squeal instability in a brake squeal simulation. Then several modified brake models were suggested and investigated how effectively they suppressed the occurrence of squeal noise. The brake parts such as a pad chamfer and a disc vane were modified and the influence of pad chamfer and vane shapes on squeal occurrence was proved to be significant. The numerical results showed that proper structural modification of a disc brake system can suppress the brake squeal to some extent.     

A cluster analysis approach for differentiating transportation modes using Bluetooth sensor data

A variety of automatic data collection technologies have been used to gather road and highway system data. The majority of these automatic data collection technologies are designed to collect vehicle-based data and either do not have the capability to collect other travel mode data (e.g., bicycles and pedestrians), or may need to be deployed differently to support this capability.

One type of wireless-based data collection system that has been deployed recently is based on Bluetooth technology. A key feature of Bluetooth-based data collection systems that makes travel mode identification feasible is that the Bluetooth-enabled devices within vehicles are also present on bicyclists and pedestrians. This research explores the effectiveness of applying cluster analysis methods when processing data collected via Bluetooth technology from vehicles, bicyclists, and pedestrians to automatically identify the associated travel modes. The results of several experiments utilizing multiple Bluetooth-based data collection units arranged linearly and in relatively close proximity on a simulated intersection demonstrate the potential of cluster analysis to accurately differentiate transportation modes from the collected data.     

Autonomous Emergency Braking Considering Road Slope and Friction Coefficient

The Autonomous Emergency Braking (AEB) systems have been actively studied for the safety enhancement and commercialized for the past few years. Because the driver tends to overly rely upon active safety systems, AEB needs to be designed to reflect the real road situations such as various road slope and friction coefficient. In this study, an AEB control algorithm is proposed to compensate for the effects of the slope and the friction of road. Based on the maximum possible deceleration for the real road conditions, the minimum braking distance is described with margin parameters for AEB activation control. The deceleration controller with a feedforward term is designed to avoid the collision during AEB operation on real road conditions. The proposed algorithm is validated in simulations first and the experimental verification is performed in the various slope conditions.     

Development of a Driving Behavior-Based Collision Warning System Using a Neural Network

An advanced driver assistance system (ADAS) uses radar, visual information, and laser sensors to calculate variables representing driving conditions, such as time-to-collision (TTC) and time headway (THW), and to determine collision risk using empirically set thresholds. However, the empirically set threshold can generate differences in performance that are detected by the driver. It is appropriate to quickly relay collision risk to drivers whose response speed to dangerous situations is relatively slow and who drive defensively. However, for drivers whose response speed is relatively fast and who drive actively, it may be better not to provide a warning if they are aware of the collision risk in advance, because giving collision warnings too frequently can lower the reliability of the warnings and cause dissatisfaction in the driver, or promote disregard. To solve this problem, this study proposes a collision warning system (CWS) based on an individual driver’s driving behavior. In particular, a driver behavior model was created using an artificial neural network learning algorithm so that the collision risk could be determined according to the driving characteristics of the driver. Finally, the driver behavior model was learned using actual vehicle driving data and the applicability of the proposed CWS was verified through simulation.     

Mean Value WGT Diesel Engine Calibration Model for Effective Simulation Research

Recently, to improve vehicle fuel economy, as well as the performance of internal combustion engines, optimized system matching between a vehicle’s drivetrain and engine has become a very important technical issue. For this reason, the need for simulation research on engine and vehicle performance improvement has increased. But in general, since both engine simulation and vehicle simulation require initial engine calibration map input, a simple engine calibration method is required for the efficient configuration of various virtual engine calibration map setups. On this background, in this study, an example of waste gate turbocharger (WGT) cooled — exhaust gas recirculation (EGR) Diesel engine calibration using a test-based mean value engine model is presented as a suitable engine calibration map setting method. Also, the feasibility of an engine calibration model is confirmed through various engine tests. Using the simple model presented here, it is possible for diverse engine operating conditions and engine performance maps to be acquired.