Operating speed pattern optimization of railway vehicles with differential evolution algorithm

The railway transportation system has much advantage in eco-friendliness, punctuality and safety compared to any other transportation system. Most of the railway system administrators have to control and operate under limited resources such as trains and facilities. It is necessary to control traveling time and energy consumption for efficient operation in the railway systems, because the board rate of passenger is inconstant with time variance. It is common that the shorter traveling time causes the greater energy consumption. In this study, a new optimization method considering operation time or energy consumption is proposed by using differential evolution algorithm and some cases are reviewed. The total energy change due to operation time variation are investigated by using the proposed optimization method for tangent and gradient track conditions. Both cases, the total energy decreases exponentially. However, because of gradient the total energy are saturated after a certain time for gradient track.     

Dual extended Kalman filter for vehicle state and parameter estimation

The article demonstrates the implementation of a model-based vehicle estimator, which can be used for combined estimation of vehicle states and parameters. The estimator is realised using the dual extended Kalman filter (DEKF) technique, which makes use of two Kalman filters running in parallel, thus 'splitting' the state and parameter estimation problems. Note that the two problems cannot be entirely separated due to their inherent interdependencies. This technique provides several advantages, such as the possibility to switch off the parameter estimator, once a sufficiently good set of estimates has been obtained. The estimator is based on a four-wheel vehicle model with four degrees of freedom, which accommodates the dominant modes only, and is designed to make use of several interchangeable tyre models. The paper demonstrates the appropriateness of the DEKF. Results to date indicate that this is an effective approach, which is considered to be of potential benefit to the automotive industry.     

Influence of load and inflation pressure on the tyre rolling resistance

Tyre load and inflation pressure are important factors controlling rolling resistance of road vehicles. The article presents results obtained in the Technical University of Gdańsk during laboratory and road measurements of different car tyres rolling on different pavements. The knowledge of rolling resistance characteristics is important for modelling car dynamics as well as fuel consumption. It is also necessary to establish proper test conditions in the future standardized on-road method of measuring rolling resistance. The results indicate that while an increase of load always leads to the increase of rolling resistance force, the influence on Coefficient of Rolling Resistance is more complicated and unpredictable. They also indicate that tyres with high rolling resistance are more sensitive to inflation pressure changes than low rolling resistance tyres.     

Implementation of discharging/charging current sensorless state-of-charge estimator reflecting cell-to-cell variations in lithium-ion series battery packs

This paper offers novel insights to the design and implementation of an innovative state-of-charge (SOC) estimator for the lithium-ion (Li-Ion) series battery pack. The most interesting feature of this approach is that it can utilize information from each filtered terminal voltage of the Li-Ion cells connected in series for SOC estimation of the battery pack. Without actual sensing each discharging/charging current (DCC) applied to the Li-Ion cells, it is possible to extract each DCC estimation from the corresponding filtered terminal voltages with an equivalent electrical circuit model (EECM) identification of all Li-Ion cells in the battery pack. There are two advantages to SOC estimation of the battery pack with this approach. First, the proposal can be implemented simply and effectively, reducing the computational steps required for SOC estimation. By reducing computational steps, the proposal is expected to be more cost-effective. Second, the approach guarantees an improved SOC performance, even if the battery pack results in inevitable cell-to-cell variation among Li-Ion cells. Accordingly, there are fewer differences to previously estimated DCCs among Li-Ion cells. Specifically, all values from the estimated DCCs are properly compensated for by simultaneous parameter modification according to each cell’s electrochemical characteristics. Experimental results clearly demonstrate that our DCC sensorless SOC estimator provides robust SOC performance for the battery pack. This approach considered an experimental battery pack (12S1P) connected in series using 2.6 Ah LiCoO2 cells produced by Samsung SDI.     

Estimation of maximum road friction coefficient based on Lyapunov method

With the real time and accurate information of motor torque and rotation speed of the four-in-wheel-motordrive electric vehicles, a slip based algorithm for estimating maximum road friction coefficient is designed using Lyapunov stability theory. Modified Burckhardt tire model is used to describe longitudinal slip property of the tire. By introducing a new state variable, a nonlinear estimator is proposed to estimate the longitudinal tire force and the maximum road friction coefficient simultaneously. With the appropriate selection of estimation gain, the convergence of the estimation error of the tire longitudinal force and maximum road friction coefficient is proved through Lyapunov stability analysis. In addition, the error is exponentially stable near the origin. Finally the method is validated with Carsim-Simulink co-simulation and real vehicle tests under multi working conditions in acceleration situation which demonstrate high computational efficiency and accuracy of this method.     

Cycle-simulation turbulence modelling of IC engines

Numerical simulations of IC engines are of high interest for automotive engineers worldwide. The simulation models should be as fast as possible, low-computational effort and predictive tool. The correct prediction of turbulence level inside the combustion chamber of spark ignition engines is the most important factor influencing to the engine working cycle. This paper presents a development of the k-ε turbulence model applied to the commercial cycle-simulation software with the high emphasis on the intake part. The validation was performed on two engine geometries with the variation of engine speed and load comparing the cycle-simulation results of the turbulent kinetic energy and in-cylinder temperature with 3-D CFD results. In order to apply the cycle-simulation turbulence model for the simulation of entire engine map, the parameterization model of turbulence constants was proposed. The parameterized turbulence model was optimized using NLPQL optimization algorithm where the single set of turbulence model parameters for each engine was found. A good agreement of the turbulent kinetic energy during the expansion was achieved when the turbulence affects the flame front propagation and combustion rate as well.     

Clamping performance of fastener in windshield wiper assembly using theoretical and experimental methods

Improper clamping of wiper arms can cause problems in the operation of the wiper. An excessive clamping force can cause damage to the wiper arm head. On the other hand, an insufficient clamping force can cause self-loosening of the nut. Given the lack of direct research on the clamping force of the fastener in wiper assembly, this study verifies the existing clamping performance of the fastener in windshield wiper assembly by theoretical and experimental methods. The theoretical calculation results show that all the clamping performance are satisfied under the general snow load condition. However, under the critical load condition, maximum assembly preload and safety margin against slipping are in disagreement with the standard values. This problem is solved by increasing the strength grade of the bolt. The experimental results show a reducing tendency of the clamping force during the snow durability test. However, this reducing clamping force during the 60,000 test cycles is acceptable. In the case of nut reusing more than two times possibly cause a problem of its loosening because of insufficient clamping force. Therefore, it is recommended that the nut should not be reused more than two times.     

Trigger algorithm of vehicle automatic crash notification system

The Automatic Crash Notification (ACN) system is an effective technology to decrease the crash response time, improve the level of post-accident rescue and alleviate the severity of injuries. To realize this system, a vehicle terminal is developed. And based on a moving window integral algorithm, the trigger algorithm of ACN system is designed. By comparing the effect of different window widths on the trigger algorithm, we select the window width of the moving window integral algorithm as 8 ms. After system is triggered, different notify types was determined according to the change of velocity in the moving window. A sled impact simulation test shows that the impact can be identified rapidly and also the notify types can be judged by the trigger algorithm. A vehicle road test proves that the ACN system has no false trigger cases. The outcomes of this study support identifications of accidents and crash severities for both occupants and emergency centers.     

Application of a modified thermostatic control strategy to parallel mild HEV for improving fuel economy in urban driving conditions

A modified thermostatic control strategy is applied to the powertrain control of a parallel mild hybrid electric vehicle (HEV) to improve fuel economy. This strategy can improve the fuel economy of a parallel mild HEV by operating internal combustion engine (ICE) in a high-efficiency region. Thus, in this study, experiments of a parallel mild HEV were conducted to analyze the characteristics of the hybrid electric powertrain and a numerical model is developed for the vehicle. Based on the results, the thermostatic control strategy was modified and applied to the vehicle model. Also, battery protection logic by using electrochemical battery model is applied because the active usage of battery by thermostatic control strategy can damage the battery. The simulation results of the vehicle under urban driving conditions show that the thermostatic control strategy can improve the vehicle’s fuel economy by 3.7 % compared with that of the conventional strategy. The results also suggest that the trade-off between the fuel economy improvement by efficient ICE operation and the battery life reduction by active battery usage should be carefully investigated when a thermostatic control strategy is applied to a parallel mild HEV.     

Real-time empirical NO<Subscript>x</Subscript> model based on In-cylinder pressure measurements for light-duty diesel engines

This paper proposes a real-time empirical model of NO_x emissions for diesel engines. The proposed model predicts the level of NO_x emissions using an empirical model developed based on the thermal NO formation mechanism, the extended Zeldovich mechanism. Since it is difficult to consider the exact physical NO formation phenomena in real-time applications, the proposed algorithm adapts the key factors of the NO formation mechanism from the extended Zeldovich mechanism: temperature of the burned gas, concentration of the gas species, and combustion duration where NO is generated. These factors are considered in a prediction model as four parameters: exhaust gas recirculation rate (EGR rate), crank angle location of 50 % of mass fraction burned (MFB50), exhaust lambda value, and combustion acceleration. The proposed prediction model is validated with various steady engine experiments that showed a high linear correlation with the NO_x emission measured by a NO_x sensor. Furthermore, it is also validated for transient experiments.