Effect of regenerative braking energy on battery current balance in a parallel hybrid gasoline-electric vehicle under FTP-75 driving mode

In recent years, a hybrid electric vehicle (HEV) has been considered a successful technology. Especially, in case of a full HEV, the motor can drive the vehicle by itself at low velocity or assist the engine at high load. To improve the hybrid electric vehicle’s efficiency, a regenerative braking system is also applied to recover from kinetic energy. In this study, an experimental control apparatus was set up with a parallel hybrid electric vehicle mounted on a chassis dynamometer to measure ECU (engine control unit) and MCU (motor control unit) signals, including the current and state of charge in the battery. In order to analyze regenerative braking characteristics, user define braking driving cycle was introduced and carried out using different initial velocities and braking times. The FTP 75 driving cycle was then adapted under different initial SOC (state of charge) levels. The experiment data was analyzed in accordance with the vehicle velocity, battery current, instant SOC level, motor RPM, engine RPM, and then vehicle driving mode was decided. In case of braking driving cycle, it was observed that SOC were increased up to 1.5 % when the braking time and the velocidy were 6 second and 60 km/h, respectively. In addition, using the FTP 75 driving cycle, mode 1 was most frequently operated at SOC 65 conditions in phase 1. In phase 2, due to frequent stop-go hills, percentage of mode 1 was increase by 22 %. Eventually, despite of identity, it was shown that the characteristics of phase 3 differed from phase 1 due to the evanishment of the effects of initial SOCs.     

Novel large scale simulation process to support dot’s cafe modeling system

This paper demonstrates a new process that has been specifically designed for the support of the U.S. Department of Transportation’s (DOT’s) Corporate Average Fuel Economy (CAFE) standards. In developing the standards, DOT’s National Highway Traffic Safety Administration made use of the CAFE Compliance and Effects Modeling System (the “Volpe model” or the “CAFE model”), which was developed by DOT’s Volpe National Transportation Systems Center for the 2005–2007 CAFE rulemaking and has been continuously updated since. The model is the primary tool used by the agency to evaluate potential CAFE stringency levels by applying technologies incrementally to each manufacturer’s fleet until the requirements under consideration are met. The Volpe model relies on numerous technology-related and economic inputs, such as market forecasts, technology costs, and effectiveness estimates; these inputs are categorized by vehicle classification, technology synergies, phase-in rates, cost learning curve adjustments, and technology “decision trees”. Part of the model’s function is to estimate CAFE improvements that a given manufacturer could achieve by applying additional technology to specific vehicles in its product line. A significant number of inputs to the Volpe decision-tree model are related to the effectiveness (fuel consumption reduction) of each fuel-saving technology. Argonne National Laboratory has developed a fullvehicle simulation tool named Autonomie, which has become one of the industry’s standard tools for analyzing vehicle energy consumption and technology effectiveness. Full-vehicle simulation tools use physics-based mathematical equations, engineering characteristics (e.g., engine maps, transmission shift points, and hybrid vehicle control strategies), and explicit drive cycles to predict the effectiveness of individual and combined fuel-saving technologies. The Large-Scale Simulation Process accelerates and facilitates the assessment of individual technological impacts on vehicle fuel economy. This paper will show how Argonne efficiently simulates hundreds of thousands of vehicles to model anticipated future vehicle technologies.     

Development of route information based driving control algorithm for a range-extended electric vehicle

A route information based driving control algorithm was developed for an RE-EV which consists of two motorgenerators, MG1 and MG2. A threshold power which controls the engine on/off to charge the battery was obtained by an optimization process using route information, such as the vehicle velocity and altitude. The threshold power allows the vehicle to travel to the final destination while making the final battery SOC close to SOC _low. Using the threshold power, route based control (RBC) was proposed by considering the driver’s characteristics and traffic conditions using the driving data base. In addition, a relationship between the threshold power and various initial battery SOC was obtained by off-line optimization. The performance of the RBC was evaluated by simulation and human-in-the-loop simulation (HILS) for city driving. It was found from the simulation and HILS results that the RBC achieved approximately 4 % to 12 % reduction in fuel consumption compared to the existing charge depleting/charge sustaining (CD/CS) driving control.     

Kriging assisted on-line torque calculation for brushless DC motors used in electric vehicles

Torque is one of the most important control factors for a vehicle’s motion. Compared with internal combustion engines, electric motors can have a more accurate torque feedback which brings a lot of advantages to vehicle dynamics and stability control. However, motors used in electric vehicles are facing more difficult conditions than those in conventional applications, such as extreme high/low temperature changing, vibration, aging, etc. The variation of motor parameters due to harsh working conditions can lead to serious problems for motor torque estimation and thus dynamic control of electric vehicles. In this paper, a new method using kriging to estimate the back EMF and thus accurately calculate motor torque in an on-line fashion is presented. With motor speed and rotor position as inputs, kriging predicts back EMF as the output that is used to calculate the motor torque with three phase currents. Using this novel method, motor torque can be accurately calculated even facing high/low temperatures or aging conditions. Experimental tests under the high temperature have been conducted to verify the applicability of the proposed method.     

Understanding the relationships between private automobile availability, overall physical activity, and travel behavior in adults

In most developed countries motorized transportation is the dominant form of travel for long and short journeys. Transport-related physical activity (TPA), however, is advocated as an appropriate transport mode for traveling short distances. The purpose of this study is to explore the associations between private automobile availability, overall physical activity levels, and TPA engagement in the adult population. A population-representative telephone survey assessed socio-demographics, private automobile availability, overall physical activity levels, and travel to place of work/study and the convenience shop with an adult sample (n = 2,000) residing in North Shore City, Auckland, New Zealand in April 2005. The majority of respondents reported unrestricted (80%) or frequent (12%) private automobile availability. After controlling for covariates, binary logistic regression analyses revealed those with no private automobile available were less likely to be classified as sufficiently active for health benefits when compared to respondents with unrestricted private automobile availability. However, this finding was based on a small minority (4%). Also, those reporting no private automobile availability were more likely to walk or cycle to place of employment and the convenience shop when compared to those with unrestricted private automobile availability. Similar to other self-report travel and physical activity survey tools, the questionnaire used potentially did not adequately capture TPA engagement. Future TPA research needs to incorporate objective measures to address this issue.

Modelling daily activity program generation considering within-day and day-to-day dynamics in activity-travel behaviour

This paper presents a comprehensive econometric modelling framework for daily activity program generation. It is for day-specific activity program generations of a week-long time span. Activity types considered are 15 generic categories of non-skeletal and flexible activities. Under the daily time budget and non-negativity of participation rate constraints, the models predict optimal sets of frequencies of the activities under consideration (given the average duration of each activity type). The daily time budget considers at-home basic needs and night sleep activities together as a composite activity. The concept of composite activity ensures the dynamics and continuity of time allocation and activity/travel behaviour by encapsulating altogether the activity types that are not of our direct interest in travel demand modelling. Workers’ total working hours (skeletal activity and not a part of the non-skeletal activity time budget) are considered as a variable in the models to accommodate the scheduling effects inside the generation model of non-skeletal activities. Incorporation of previous day’s total executed activities as variables introduces day-to-day dynamics into the activity program generation models. The possibility of zero frequency of any specific activity under consideration is ensured by the Kuhn-Tucker optimality conditions used for formulating the model structure. Models use the concept of random utility maximization approach to derive activity program set. Estimations of the empirical models are done using the 2002–2003 CHASE survey data set collected in Toronto.

Establishing value of time for the inter-island passenger transport of the Western Visayas region,Philippines

Transportation infrastructure planning process requires cost–benefit analysis in the evaluation of project proposals. Value of time (VOT) facilitates the conversion of travel time savings, which is a significant proportion of benefits in monetary terms. In cases where VOT has not been established, planners resort to crude estimates that often results in erroneous or biased measurements of benefits. This is the case of the Western Visayas region in the Philippines where transportation studies are rare. Secondary cities and its peripheral regions have often been overlooked subjects of transportation studies. In this study, multinomial logit models using revealed preference data were estimated to facilitate the calculation of the VOT. The total cost, square of the total cost, and total time were identified as significant explanatory variables affecting mode choice. The square of the total cost term was introduced in the models in order to account for income effect. Results indicate that VOT estimates for the inter-island passenger transportation between Iloilo and Negros Occidental generally range from 78.15PHP to 179.15PHP (1.91USD to 4.37USD) depending on trip and traveller characteristics.     

New routes on old railways: increasing rail’s mode share within the constraints of the existing railway network

This paper describes an integrated methodology for identifying potential ‘quick wins’ for mode shift from road to passenger rail transport. Firstly, a procedure for analysing rail’s relative competitiveness in the market for passenger transport between large urban areas is developed and then applied to a UK case study. The purpose of such analysis is to allow the identification of flows where rail is currently relatively uncompetitive (in terms of journey time in particular) and to assess the reasons for this poor performance, so that the issues which suppress rail use may be addressed. In parallel, a framework, methodology and tool for the assessment of existing and potential capacity (trains, seats, TEUs, etc.) is developed for both passenger and freight traffic, to identify and address network constraints. An illustrative example of the use of these demand and capacity assessment tools is then presented, with the tools used to identify and evaluate flows where rail demand is suppressed by poor service quality and where spare capacity exists which would allow the passenger rail service to be improved without requiring significant investments in infrastructure. The effects of such improvements on demand are predicted, and the cost implications of operating such additional services are discussed. The analysis suggests that there may be significant potential for increasing rail’s mode share by providing additional inter-urban services where rail currently offers an inferior service.     

Community Severance: Where Is It Found and at What Cost?

Community severance occurs when transport infrastructure or motorised traffic divides space and people. Despite the growing awareness of its effects on the wellbeing of local communities, the problem is not usually assessed quantitatively or assigned a monetary value. This paper reviews existing practice and research on quantitative methods dealing with community severance. The problem is first decomposed into a series of questions, which are then used as a base to review the methods found in governmental guidance documents, technical reports, and academic studies. The paper ends with recommendations for the integration of severance issues into transport planning.