Bees-algorithm-based optimization of component size and control strategy parameters for parallel hybrid electric vehicles

This paper presents the optimization of key component sizes and control strategy for parallel hybrid electric vehicles (parallel HEVs) using the bees algorithm (BA). The BA is an intelligent optimization tool that mimics the food foraging behavior of honey bees. Parallel HEV configuration and electric assist control strategy were used to conduct the research. The values of the key component size and the control strategy parameters were adjusted according to the BA to minimize the weighted sum of fuel consumption (FC) and emissions, while the vehicle performance satisfies the PNGV constraints. In this research, the software ADVISOR was used as the simulation tool, and the driving cycles FTP, ECE-EUDC and UDDS were employed to evaluate FC, emission and dynamic performance. The results demonstrate that the BA is a powerful tool in parallel HEV optimization to determine the optimal parameters of component sizes and control strategy, resulting in the improvement of FC and emissions without sacrificing vehicle performance. In addition, the BA is able to define a global solution with a high rate of convergence.     

Optimized dynamic battery model suited for power based vehicle energy simulation

Ever increasing demand for the petroleum is causing faster than expected oil shortages in the supply and demand balance around the world and furthermore, many specialists in the field of oil production such as Association for the Study of Peak Oil and World Energy Outlook are claiming that the petroleum is around the peak of its production (Figure 1). Such shortage made the greatest impact on the gasoline price hikes at the gas pump and thus, this impact was felt by the consumers severely and became the greatest motivation for automotive industries to strive to pioneer the researches for the next generation vehicle configurations ranging from HEV, PHEV, Pure EV to FCHEV (collectively noted as xEV). While the great deal of researches has been carried over the last few decades, it is still far from mass productions for consumer use except for the HEV mainly due to the high cost involved with other types of xEV configurations. Therefore, it is critical to design the vehicle to maximize the use of each component at its highest point regardless of any cost scenarios and it is clear that this optimization can only be achieved through the accurate energy balance simulation for a specific target vehicle prior to the actual hardware implementation. In this paper, it is our intention to introduce modified dynamic battery modeling scheme that would provide a more accurate way of simulating the battery behavior when used in the vehicle energy simulation system. Starting from a typical battery dynamic model to predict the voltage given an imposed current request, we have introduced a new scheme to establish the relationship between the voltage and the power (rather than the current) requested by the vehicle simulation system. The proposed scheme handles the power request from the vehicle simulator considering the dynamic battery characteristics and in turn, contributes to the better estimation of the current integrated energy usage and battery SOC level in the given battery dynamic system used in the vehicle energy simulation system.     

Electro-hydraulic braking system for autonomous vehicles

Reducing the number of traffic accidents is a declared target of most governments. Since dependence on driver reaction is the main cause of road accidents, it would be advisable to replace the human factor in some driving-related tasks with automated solutions. To automate a vehicle, it is necessary to control the actuators of a car, i.e., the steering wheel, accelerator, and brake. This paper presents the design and implementation of an electro-hydraulic braking system consisting of a pump and various valves, allowing the control computer to stop the car. It is assembled in conjunction with the original circuit for the sake of robustness and to permit the two systems to halt the car independently. This system was developed for installation in a commercial Citroën C3 Pluriel of the AUTOPIA program. Various tests were carried out to verify its correct operation, and an experiment showing the integration of the system into the longitudinal control of the car is described.     

Analytical study on the performance of a high power pretensioner

In this paper, a numerical procedure to estimate the performance of the high power pretensioner used in the seatbelt of a passenger vehicle is presented. The data on the gas explosion pressure in a 10-cc volume and the data on the displacement of the rack according to time were applied to the numerical procedure. The procedure was implemented using MATLAB. The testing device, which met the automobile industry standards, was created. Experiments were carried out seven times under the same conditions, and the mean values of the web retraction and belt load were used as the representative data. By comparing the simulation results to the test results, the numerical procedure presented in this paper was verified.     

潮湿路面滑水现象及抗滑力模型

滑水及抗滑力的衰减是潮湿条件下影响道路及机场跑道交通安全的两个重要因素。模拟潮湿路面抗滑力是一个相对复杂的问题。笔者采用理论研究方法,提出了一个分析计算模型,用来模拟车轮滑移速度增加时,潮湿路面的滑水现象及抗滑力的衰减情况。该理论公式及三维有限元模型的理论基础是固体力学及流体动力学。通过NASA滑水速度方程,对模型计算的滑水速度进行分析验证。     

The validity of using activity type to structure tour-based scheduling models

A unique set of activity scheduling data is utilized in this paper to provide much needed empirical analysis of the sequence in which activities are planned in everyday life. This is used to assess the validity of the assumption that activities are planned in accordance to a fixed hierarchy of activity types: mandatory activities first (work/school), followed by joint maintenance, joint discretionary, allocated maintenance, and individual discretionary activities. Such an assumption is typical of current generation activity and tour-based travel demand models. However, the empirical results clearly do not support such assumptions. For instance, fewer than 50% of mandatory activities were actually planned first in related out-of-home tours; remaining activity types also did not take any particular precedence in the planning sequence. Given this, a search was made for the more salient attributes of activities (beyond activity type) that would better predict how they are planned within tours. Several ordered response choice models for different tour sizes were developed for this purpose, predicting the choice order of the 1st, 2nd, 3rd, etc. planned activity in the tour as a function of activity type, activity characteristics (duration, frequency, travel time, and involved persons), and individual characteristics. Activity duration played the most significant role in the models compared to any other single variable, wherein longer duration activities tended to be planned much earlier in tours. This strongly suggests that the amount of time-use, rather than the nature of the event as indicated by activity type, is a primary driver of within-tour planning order and offers potential for a much improved and valid fit.     

Improvement of Vehicle Dynamics by Rear Braking Force Control

A study on effective use of rear braking force to improve a brake performance and vehicle dynamics are carried out. On a ordinary condition, the rear braking force could be more increased to a conventional braking force distribution. Based on this thought, the brake performances are estimated. The results show the effects not only improve the brake performance but also reduce a pitching at braking and moderate a vehicle OS behavior in a turn during braking. These are verified by experimental test vehicle equipped with a rear braking force control system.     

Application of Learning Automata to Controller Design in Slow-Active Automobile Suspensions

This study considers a new design methodology in the context of active vehicle suspension control. The approach combines concepts from Stochastic Optimal Control with those of Learning Automata. A learning automaton effectively learns optimal control on-line in the vehicle, in an appropriate stochastic “test-track” environment. For practical application, the overwhelming advantage of this approach is that no explicit modelling is required, and considerable time savings may be expected in system development. This simulation study considers the on-line learning of optimal control in a low-bandwidth active suspension system, where control feedback is confined to a body-mounted accelerometer at each corner of the vehicle. It is shown that learning can successfully take place under a range of conditions, including the case when there is substantial transducer noise. The performance of the resulting control system is shown to depend heavily on the nature of the learning environment.     

永久磁铁励磁的牵引电动机

极对数多的永磁牵引电动机使不用传动齿轮箱的电传动成为可能.与用传动齿轮箱的相比,它重量轻,且效率高.文章简要介绍永磁同步电机和永磁横向磁通电机,以及它们在试验台上的成功试验.