Selection of Actuator Combination in Integrated Chassis Control Using Taguchi Method

This paper presents a method to select the actuator combination in integrated chassis control using Taguchi method. Electronic stability control (ESC), active front and rear steering (AFS/ARS) are used as an actuator, which is needed to generate a control tire force. After computing the control yaw moment in the upper-level controller, it is distributed into the control tire forces, generated by ESC, AFS and ARS in the lower-level controller. In this paper, the weighted pseudo-inverse control allocation (WPCA) with variable weights is used to determine the control tire forces of each actuator. Taguchi method is adopted for sensitivity analysis on variable weights of WPCA in terms of the control performances such as the maneuverability and the lateral stability. For sensitivity analysis, simulation is performed on a vehicle simulation package, CarSim. From sensitivity analysis, the most effective actuator combination is selected.     

Mixed Harmonic Runnable Scheduling for Automotive Software on Multi-Core Processors

The performance of automotive electronic control units (ECUs) has improved following the development of multi-core processors. These processors facilitate fast computing performance without increasing clock speed. System developers partition automotive application runnables to have parallelizability and avoid interference between various software modules. To improve the performance of such systems, an efficient scheduler is necessary. In this regard, for multi-core ECUs, the automotive open system architecture (AUTOSAR) suggests partitioned static priority scheduling for parallelized software. In the AUTOSAR approach, clustering and partitioning of runnables for specific cores becomes difficult, but there is no exact criterion followed for partitioning the runnables. Consequently, cores are not balanced against loads, and under contingency conditions, there is a chance that tasks will miss deadlines. In this study, we address this problem by exploring a mixed harmonic runnable scheduling algorithm that includes partitioned scheduling. We tested this algorithm using high load conditions under contingency consequences, and we evaluated it using models of periodic runnables, periodic interrupts, and event-triggered interrupts. The performance parameters considered in this paper are balancing performance and the deadline missing rate. Our results indicate that the proposed algorithm can contribute toward improving the functional safety of vehicles.     

Model Predictive Coordinated Control for Dual-Mode Power-Split Hybrid Electric Vehicle

Power-split hybrid electric vehicles (HEVs) have great potential fuel efficiency and have attracted extensive research attention with regard to their control system. The coordinated controller in HEV plays an important role in tracking the optimal state reference generated by the energy management strategy (EMS), so as to reach the desired fuel efficiency. Meanwhile, the coordinated controller also has a significant impact on driving performance. To improve its performance, the design of a model predictive control (MPC) based coordinated controller in power-split HEV is presented. First, a non-linear, time-varying constrained control oriented transmission model of a dual-mode power-split HEV is formulated to describe this control problem. Then, to solve this problem, the non-linear part in the transmission model is linearised, and a linear MPC is used to obtain the control signals for the motors and engine at each time step. To meet the requirements of real-time computation, a fast MPC method is also applied to reduce the online computation effort. Simulations and experiments demonstrate the effectiveness of the proposed MPC-based coordinated controller.     

Iterative Learning Control Algorithm for Feedforward Controller of EGR and VGT Systems in a CRDI Diesel Engine

The modern diesel engines equip the exhaust gas recirculation (EGR) system to suppress the NOx emissions. In addition, the variable geometric turbocharger (VGT) system is installed to improve the drivability and fuel efficiency. These EGR and VGT systems have cross-coupled behavior because they interact with the intake and the exhaust manifolds. Furthermore, the turbocharger time delay, gas flow dynamics through EGR pipe cause the nonlinearity characteristics. These nonlinear multi-input-multi-output characteristics cause the degradation of control accuracy, especially during the transient condition. In order to improve the control accuracy, this study proposes an iterative learning control (ILC) algorithm for feedforward controller of EGR and VGT systems. The feedforward controller obtains the values about EGR and VGT actuators using the previous control results in predefined transient states. The ILC algorithm consists of a PD-type learning function and a low-pass filter. The control gains of learning function are determined to guarantee the convergence of learning results. In addition, the low-pass filter is designed for robustness against plant disturbance. The proposed control algorithm was validated by engine experiment which repeated predefined transient states. The error was reduced by 15 % according to the gain. As a result, the proposed algorithm is affordable for improving the transient control performance.     

Potential of Real-Time Cylinder Pressure Analysis by Using Field Programmable Gate Arrays

In this paper, a Field Programmable Gate Array (FPGA) was used to implement a real-time cylinder pressure analysis. The goal of the project was to improve the accuracy of calculated heat release and center of combustion calculations to enhance the precision of engine control functions. Compared to today’s real-time pressure analysis systems, several additional physical effects were taken into account for this objective. The wall heat transfer was calculated based on the approach published by Hohenberg. A chemical equilibrium with six substances was assumed for the mixture composition and a real-time calculation method was developed. Furthermore, a two-zone model was adapted and implemented for this realtime analysis. The validation of the results and the rating of the improvement in precision were based on GT-SUITE simulation results as an offline reference tool. Compared to state-of-the-art analysis systems, it was possible to reduce the average error of the center of combustion position from 1.6° to 0.5° crank angle (CA) by taking the investigated effects into account. Moreover, it was possible to significantly reduce the time required for the calculation from one complete combustion cycle to 0.2°CA at an engine speed of 3,000 rpm by using a continuous calculation method on the FPGA. This led to an additional improvement of the ability to control the engine, especially under highly dynamic operation conditions.     

Load Transfer Analysis of a Bus Bay Section Under Standard Rollover Test Using <Emphasis Type="Italic">U</Emphasis>*<Subscript>M</Subscript> Index

Bus rollover accidents are receiving increasing attention due to the associated high fatality rate. In order to improve the bus structural performance during the rollover collision, it is necessary to investigate how the impact force is transferred within the bus superstructure. This paper introduced a method for studying the load transfer behavior of the bus superstructure during the standard rollover test by using the U * _M index. A bus bay section was used as the sample structure to demonstrate the proposed method. The result of the paper reveals that the load transfer analysis based on the U * _M index can provide engineers with the insight of the structural issues and the direction to improve the structural performance, which cannot be accomplished through the conventional finite element analysis.     

Effects of Injection Timing on Transient Performance of A Regulated Two-Stage Turbocharged Diesel Engine with Turbine Bypass Valve

The object of this paper is to reduce soot emissions under typical 5s transient conditions of constant speed and increasing torque. And effects of fuel injection timing on combustion and emissions parameters were experimentally and numerically studied in a regulated two-stage turbocharged diesel engine with a turbine bypass valve (TBV). The test results indicated that: the smaller TBV opening could improve deterioration of smoke emissions and BSFC at medium and heavy loads. Afterward, the full-stage injection timing (FSIT) strategies (delaying injection timing during the entire transient process) could reduce soot and NO_X emissions simultaneously. However, when TBV opening became larger, smoke emissions and BSFC were deteriorated gradually. Moreover, the sectional-stage injection timing (SSIT) strategies (advancing injection timing from 10 % load to a preset load and delaying injection timing from the preset load to 100 % load) could markedly reduce soot emissions by 75.8 % with TBV opening 20 %; the degradation of fuel consumption could be effectively suppressed. Finally, coupling the SSIT strategies with the TBV control strategies could significantly improve the transient performance.     

Development of a Driving Behavior-Based Collision Warning System Using a Neural Network

An advanced driver assistance system (ADAS) uses radar, visual information, and laser sensors to calculate variables representing driving conditions, such as time-to-collision (TTC) and time headway (THW), and to determine collision risk using empirically set thresholds. However, the empirically set threshold can generate differences in performance that are detected by the driver. It is appropriate to quickly relay collision risk to drivers whose response speed to dangerous situations is relatively slow and who drive defensively. However, for drivers whose response speed is relatively fast and who drive actively, it may be better not to provide a warning if they are aware of the collision risk in advance, because giving collision warnings too frequently can lower the reliability of the warnings and cause dissatisfaction in the driver, or promote disregard. To solve this problem, this study proposes a collision warning system (CWS) based on an individual driver’s driving behavior. In particular, a driver behavior model was created using an artificial neural network learning algorithm so that the collision risk could be determined according to the driving characteristics of the driver. Finally, the driver behavior model was learned using actual vehicle driving data and the applicability of the proposed CWS was verified through simulation.     

Lifting Capability and Stress Analyses of the Crane System for a Large-Sized Tactical Wrecker

A large-sized tactical wrecker is a special-purpose vehicle that lifts and tows tactical vehicles and heavy loads. It consists of a crane, a post structure, outriggers and a suitable chassis truck, and during its initial design, the structural safety and tipping stability should be preemptively examined in terms of the layout of these components. This paper proposes computer-aided engineering (CAE) methods to evaluate the maximum lifting capacity of the wrecker and the structural safety of its crane during the initial design. The analytical model for the large-sized wrecker is constructed with 236 degrees of freedom by combining the crane system developed using the ADAMS macros with the dynamic model of large chassis truck with an axle suspension. The design parameters for the wrecker model that influence the tipping stability are selected, and then the maximum lifting loads with the corresponding changes are calculated. This parametric study shows that the characteristics of the boom and the layout of the outriggers greatly affect the maximum lifting capacity. Finite element (FE) analyses of the 1st stage boom and the 3rd stage boom show the stresses under the maximum overturning moment condition are within the allowable strength.     

DC Motor Current Control Algorithm Using Proportional-Integral LQT with Disturbance Observer

This paper proposes a DC motor current control algorithm using a proportional-integral linear quadratic tracking (LQT) controller with a disturbance observer for the electronic stability control (ESC) brake system. Previously researched algorithms related to current control using disturbance rejection are robust control, adaptive control, LQT, or proportional-integral disturbance observer (PI-DOB); each of them has both advantages and disadvantages. The proposed algorithm uses a disturbance observer in order to improve disturbance rejection performance while avoiding the drawbacks of high gain property. Additionally, the proposed algorithm adds integral control in order to improve performance in the low frequency bands. In order to assess the performance of the proposed algorithm, simulations and experiments are performed in the time and frequency domains to compare the proposed algorithm with different algorithms which are actually implemented into the ESC. The proposed algorithm shows good characteristics near the cut-off frequency, which can be confirmed clearly by the time domain results.