Experimental research of the EQ6110HEV hybrid electric bus using an on-line debugging system

This paper describes the on-line debugging software developed by our research team. The software has five functions and can be helpful in achieving rapid development for hybrid electric buses. In addition, the software can monitor system states continuously and also modify parametric maps or update control programs using its on-line programming function. Based on the on-line debugging system, the hybrid propulsion control system is designed, and all the working modes of the hybrid electric bus are tested. Finally, experiments are carried out that verify that the debugging system is feasible and reliable. The test results show that the hybrid electric bus can reduce fuel consumption by about 19.1 percent, in comparison with conventional buses.     

Fault detection method for electric parking brake (EPB) systems with sensorless estimation using current ripples

A fault detection method with parity equations is proposed in this paper. Due to its low cost implementation, the velocity of the motor is not measurable in electric parking brake (EPB) systems. Therefore, residuals are not reliable when estimating the motor velocity with a low-resolution encoder. In this paper, we propose a fault detection method with sensorless estimation using current ripples that estimates the position and velocity of the motor by detecting periodical oscillations of the armature current caused by rotor slots. In addition, this method can estimate the position and velocity of the motor with less computational effort than a state observer. Moreover, the method is less sensitive to motor parameters than model-based estimation methods. The effectiveness of this method is validated with experimental data, and the simulation results show that various faults have their own residual patterns. Therefore, we can detect the presence of faults by monitoring the residual signals.     

Development of electrostatic diesel particulate matter filtration systems combined with a metallic Flow-Through Filter and electrostatic methods

A 3000 cc diesel engine attached to an engine dynamo was used to test three newly developed electrostatic Diesel Particulate matter filtration Systems (DPS 1, 2, and 3) under four steady-state engine operating conditions: idle, 2000 rpm with no load, and 2000 rpm under 25% and 50% loads. Of the two developed alternatives, DPS 1 and DPS 2, DPS 2 comprises an ionization section, electrostatic field additional section and Flow-Through Filter (FTF), which achieved almost 90% removal of particulate matter (PM) under the engine’s operating conditions, and the efficiency of the FTF was maintained between 20% and 50%. Comparing the long-term performance of DPS 2 and DPS 3 (effectively a serial combination of two DPS 2s) with a commercially-available Diesel Particulate Filter (DPF), the DPS 2 and DPS 3 achieved almost the same efficiency for removing PM as the DPF but had significantly improved (75%∼90% lower) differential pressure drops.     

Application of slim A-pillar to improve driver’s field of vision

The importance of vehicle safety cannot be exaggerated in today’s mobile societies. Many manufacturers, associates related to vehicles and universities make an effort to improve vehicle safety by developing new technologies, applying high strength steel to the body structure etc. However, the majority of these efforts are focused on decreasing injury. It is absolutely important to minimize injury, but a more important aspect is coping with vehicle accidents. That is, As undeniably important as it is to minimize potential injuries, it is critical that experts focus on developing ways to keep drivers out of situations likely to lead to crashes in the first place. The purpose of this paper is to determine what the most critical factor is when coping with an unfamiliar driving situation. The answer is to provide a wide-open field of vision, especially for the driver. The driver’s field of vision is obstructed by the vehicle’s A-pillar. To solve this, the A-pillar obstruction angle, which is the angle between the driver’s eyes and the A-pillar should be decreased. This paper purposes three-methods for decreasing this angle structurally and applying a slim A-pillar which is as the best solution to decrease the A-pillar obstruction angle and ensure the drivers field of vision at the same time     

Design and implementation of a new clamping force estimator in Electro-Mechanical Brake systems

In this paper, an improved clamping force estimator is proposed for Electro-Mechanical Brake (EMB) systems by using the motor rotor position information and the hysteresis characteristics of mechanical parts in the EMB. A cascaded type of a force/position control system with a force sensor or an estimator was designed and implemented to control the clamping force and to keep the clearance gap in EMB systems. The EMB Hardware-In-the-Loop-Simulation (HILS) results show that the proposed force estimator yields better estimation performance than the existing estimator and that the clamping force control system based on the estimator can be also used for the fault tolerant control of the system.     

Artificial neural network approach to study the effect of injection pressure and timing on diesel engine performance fueled with biodiesel

This study intends to predict the influence of injection pressure and injection timing on performance, emission and combustion characteristics of a diesel engine fuelled with waste cooking palm oil based biodiesel using the artificial neural network (ANN) model. To acquire data for training and testing in the proposed ANN, experiments were carried out in a single cylinder, four stroke direct injection diesel engine at a constant speed of 1500 rpm and at full load (100%) condition. From the experimental results, it was observed that waste cooking palm oil methyl ester provided better engine performance and improved emission and combustion characteristics at injection pressure of 280 bar and timing of 25.5° bTDC. An ANN model was developed using the data acquired from the experiments. Training of ANN was performed based on back propagation learning algorithm. Multilayer perceptron (MLP) network was used for non-linear mapping of the input and output parameters. Among the various networks tested the network with two hidden layers and 11 neurons gave better correlation coefficient for the prediction of engine performance, emission and combustion characteristics. The ANN model was validated with the test data which was not used for training and was found to be very well correlated.     

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.     

Multi-axle vehicle dynamics stability control algorithm with all independent drive wheel

The stability driving characteristic and the tire wear of 8-axle vehicle with 16-independent driving wheels are discussed in this paper. The lateral stability of 8-axle vehicle can be improved by the direct yaw moment which is generated by the 16 independent driving wheels. The hierarchical controller is designed to determine the required yaw torque and driving force of each wheel. The upper level controller uses feed-forward and feed-backward control theory to obtain the required yaw torque. The fuzzification weight ratio of two control objective is built in the upper level controller to regulate the vehicle yaw and lateral motions. The rule-based yaw moment distribution strategy and the driving force adjustment based on the safety of vehicle are proposed in the lower level controller. The influence of rear steering angle is considered in the distribution of driving force of the wheel. Simulation results of a vehicle double lane change show the stability of 8-axle vehicle under the proposed control algorithm. The wear rate of tire is calculated by the interaction force between the tire and ground. The wear of tire is different from each other for the vehicle with the stability controller or not.