Design and validation of an electro-hydraulic brake system using hardware-in-the-loop real-time simulation

This paper presents a novel electric booster (E-booster) that exibits superior performance advantages over traditional vacuum boosters. The proposed E-booster, consisting of an electric motor and a ball screw assembly, is designed for electro-hydraulic brake (EHB) systems to meet relevant requirements for electric vehicles and active safety technologies. A mathematical model for an EHB system is generated to determine the desired values of the parameters for the E-booster prototype using numerical simulation in MATLAB. Simulation results of the EHB system with the virtual E-booster demonstrate the feasibility and effectiveness of the innovative technique. Built upon the results derived from the numerical simualtions, an integrated algorithm based on the Kalman filter and a sliding mode control technique is designed to control the E-booster motor and to implement the brake booster function. A hardware-in-the-loop (HIL) real-time simulation system equipped with the E-booster prototype is developed. HIL real-time simulations are conducted to evaluate the proposed algorithm. The HIL real-time simulation results demonstrate that the proposed algorithm generates booster brake forces fast, and forces the ball nut to track the push rod well to ensure comfortable brake pedal feel.     

Calibration efficiency improvement of rule-based energy management system for a plug-in hybrid electric vehicle

This paper presents a calibration method of a rule-based energy management strategy designed for a plug-in hybrid electric vehicle, which aims to find the optimal set of control parameters to compromise within the conflicting calibration requirements (e.g. emissions and economy). A comprehensive evaluating indicator covering emissions and economy performance is constructed by the method of radar chart. Moreover, a radial basis functions (RBFs) neural network model is proposed to establish a precise model within the control parameters and the comprehensive evaluation indicator. The best set of control parameters under offline calibration is gained by the multi-island genetic algorithm. Finally, the offline calibration results are compared with the experimental results using a chassis dynamometer. The comparison results validate the effectiveness of the proposed offline calibrating approach, which is based on the radar chart method and the RBF neural network model on vehicle performance improvement and calibrating efficiency.     

Cyclist target and test setup for evaluation of cyclist-autonomous emergency braking

From 2018, Autonomous Emergency Braking (AEB) systems dedicated to avoid or mitigate passenger car-tocyclist collisions will be considered in the safety assessment by Euro NCAP. To test such systems, appropriate equipment has been developed in a project called CATS “Cyclist-AEB Testing System”, that has run between April 2014 and August 2016. Moreover, a proposal for the most relevant test scenarios was set up. The objective of the project was to provide proof to Euro NCAP of the relevance of the proposed test scenarios and of the feasibility of practical implementation of the scenarios and test setup. The process regarding the selection, verification and validation of test scenarios is described. The cooperation between 17 industrial partners (car manufacturers and automotive suppliers) in the CATS project has stimulated the harmonization and acceptance of the protocol, target and test setup. The process and intermediate results including the used methodology, have been reviewed by the German Federal Highway Research Institute (BASt) and have been shared on a regular basis during the project with stakeholders in Europe, Japan and the USA. Euro NCAP already indicated to consider the results of the CATS project as the main input to draft the test protocol, including scenarios and target for Cyclist-AEB systems in 2018 and 2020.     

MPC-BASED steering control for backward-driving vehicle using stereo vision

We propose a steering control algorithm for autonomous backward driving in a narrow corridor. Passable spaces are detected using a stereo camera, and the steering angle is controlled by a model predictive controller (MPC). For passable space detection, an UV-disparity map is calculated from the original disparity map. Information regarding passable spaces collected by the stereo camera is used in steering control. Backward driving requires the driver’s preemptive actions, which can be learned by experience because of the non-intuitive responses (the initial motion of the vehicle is opposite to the driver’s steering angle input). This occurs because a backward-driving vehicle is a non-minimum phase system. One of the most popular steering control algorithms is Stanley method, which is based on the feedback of lateral displacement error and heading angle error. The method is very intuitive and works well for forward driving, but it exhibits significant undershoot for backward driving cases. Furthermore, the method does not explicitly consider any constraints on control inputs and states. We designed a steering controller based on the MPC technique that requires future information but can handle constraints explicitly. Because we have near-future information from the stereo camera under limited passable spaces, MPC can be effectively implemented. We performed several simulations and experiments to show the performance and superiority of the suggested method over a simple feedback-based control algorithm.     

Analysis of solution findings in the conceptual design of function structures

In the conceptual stage the function design process is realized by the computer aided application. After surveying on the function specification methods and the function modeling, a computer aided function design environment is analyzed. Subsequently based on a module library and principle catalogue, a solution finding process as a part of conceptual design is proposed for a creative design. In addition, a search algorithm to find the solution of adaptable function structure is also discussed. The concepts proposed in this paper can support the subsequent design stages, especially simulation for checking the function structure defects.     

Performance comparison of multicast routing protocols based on NS-2

The electronic system in a comprehensive shipboard has a extremely wide bandwidth. It supports synchronized and asynchronous data transmission, multimedia correspondence, and videophone conferencing. In order to guarantee the security and correspondent real time of the communication, choosing a multicast routing protocol based on different applications is a key problem in terms of the complexity of the system. A simulation model was first designed for existing multicast routing protocols in NS-2 and analysis was performed on their corresponding application environments. The experiments proved that PIM-DM based on the shortest-path tree protocol is suitable for communication in the field of comprehensive shipboard. Further work that is necessary is also discussed.     

The relative importance of price and driving range on electric vehicle adoption: Los Angeles case study

Electric vehicles (EVs) are still a maturing technology. Barriers to their adoption include price and range anxiety. EV batteries are significant in determining both EV prices and costs. In this work, we focus on the impact of a high-capacity battery and EV rebates on an EV ecosystem. Using survey data from Los Angeles, California, we simulate different cases of battery costs and prices by means of an agent-based EV ecosystem model. We find that even in Los Angeles, a geographically spread out city, the price of EVs is a more significant barrier to adoption than EV range. In fact, even a quintupling of battery size at no additional costs improves EV adoption by only 5 %. Therefore, policy makers should focus more on affordability than range in promoting EV adoption.     

A dynamic approach to road freight flows modeling in Spain

This paper presents an innovative approach to analyzing road vehicle freight traffic that uses a dynamic panel data specification derived from a gravity model. This dynamic approach, which has recently been employed in international goods trade models in lieu of the traditional static specification, is applied to the case of Spain using data for the countrys 15 NUTS-3 regions between 1999 and 2009. Using the system general method of moments approach, we obtained significant evidence that the flow of vehicles carrying commodities by road has a strong persistence effect when controlling for unobserved heterogeneity. We also found that the quality of road transport infrastructure has a significant impact on vehicle trips. According to our findings, we suggest that this type of specification be employed in distribution models in which fixed effects and lags of the dependent variable are included to account for unobserved heterogeneity and persistence effects, respectively.     

Impact of family in-home quality time on person travel demand

This paper introduces the concept of Primary Family Priority Time (PFPT), which represents a high priority household decision to spend time together for in-home activities. PFPT is incorporated into a fully specified and operational activity based discrete choice model system for Copenhagen, called COMPAS, using the DaySim software platform. Structural tests and estimation results identify two important findings. First, PFPT has a place high in the model hierarchy, and second, strong interactions exist between PFPT and the other day level activity components of the model system. Forecasts are generated for a road pricing and congestion scenario by COMPAS and a comparison version of the model system that excludes PFPT. COMPAS with PFPT exhibits less mode changing and time-of-day shifting in response to pricing and congestion than the comparison version.     

Travel mode choice and travel satisfaction: bridging the gap between decision utility and experienced utility

Over the past decades research on travel mode choice has evolved from work that is informed by utility theory, examining the effects of objective determinants, to studies incorporating more subjective variables such as habits and attitudes. Recently, the way people perceive their travel has been analyzed with transportation-oriented scales of subjective well-being, and particularly the satisfaction with travel scale. However, studies analyzing the link between travel mode choice (i.e., decision utility) and travel satisfaction (i.e., experienced utility) are limited. In this paper we will focus on the relation between mode choice and travel satisfaction for leisure trips (with travel-related attitudes and the built environment as explanatory variables) of study participants in urban and suburban neighborhoods in the city of Ghent, Belgium. It is shown that the built environment and travel-related attitudes—both important explanatory variables of travel mode choice—and mode choice itself affect travel satisfaction. Public transit users perceive their travel most negatively, while active travel results in the highest levels of travel satisfaction. Surprisingly, suburban dwellers perceive their travel more positively than urban dwellers, for all travel modes.