Comparative investigation on the aerodynamic effects of combined use of underbody drag reduction devices applied to real sedan

To reduce the aerodynamic drag, the performance of the underbody aerodynamic drag reduction devices was evaluated based on the actual shape of a sedan-type vehicle. An undercover, under-fin, and side air dam were used as the underbody aerodynamic drag reduction devices. In addition, the effects of the interactions based on the combination of the aerodynamic drag reduction devices were investigated. A commercial sedan-type vehicle was selected as a reference model and its shape was modeled in detail. Aerodynamic drag was analyzed by computational fluid dynamics at a general driving speed on highway of 120 km/h. The undercover reduced the slipstream area through the attenuation of the longitudinal vortex pair by enhancing the up-wash of underflow, thereby reducing the aerodynamic drag by 8.4 %. The under-fin and side air dam showed no reduction in aerodynamic drag when they were solely attached to the actual complex shape of the underbody. Simple aggregation of the effects of aerodynamic drag reduction by the individual device did not provide the accurate performance of the combined aerodynamic drag reduction devices. An additional aerodynamic drag reduction of 2.1 % on average was obtained compared to the expected drag reduction, which was due to the synergy effect of the combination.     

The impact of route guidance,departure time advice and alternative routes on door-to-door travel time reliability: Two data-driven assessment methods

ABSTRACT

Conventional travel time reliability assessment has evolved from road segments to the route level. However, a connection between origin and destination usually consists of multiple routes, thereby providing the option to choose. Having alternatives can compensate for the deterioration of a single route; therefore, this study assesses the reliability and quality of the aggregate of the route set of an origin-destination (OD) pair. This paper proposes two aggregation methods for analyzing the reliability of travel times on the OD level: 1) an adapted Logsum method and 2) a route choice model. The first method analyzes reliability from a network perspective and the second method is based on the reliability as perceived by a traveler choosing his route from the available alternatives. A case study using detailed data on actual travel times illustrates both methods and shows the impact of having variable departure times and the impact of information strategies on travel time reliability.     

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.     

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.     

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.     

Electrically Assisted Internal Combustion Engines: A Comparative Analysis

An electrically assisted internal combustion engine is obtained by combining a conventional engine and one or more electrical motors of considerably smaller size. A key feature of such an innovative vehicle hybridization approach is that the torque generated by electric machines is not transmitted to the wheels. The electric motors are, in fact, intended only to assist the internal combustion engine in low efficiency, low performance, or high polluting working conditions. They however, draw extra power and energy from the battery. This paper presents a tool to evaluate different possible solutions in terms of energy balance, efficiency, battery stress and battery ageing. The method, which is based on suitable mathematical models and specific analysis criteria is also exploited to compare eight different configurations of a C-segment vehicle, pointing out limits and capabilities of traditional 12?14 V systems.     

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.     

Development of an Operability Evaluation Framework for Remotely Controlled Ground Combat Vehicles in a Simulated Environment

This paper proposes a systematic framework for operability evaluation of remotely controlled ground combat systems (RGCS) in a simulated environment. The popular human-robot interaction metric used in unmanned vehicle systems is called fan-out (FO) and represents the maximum number of robots/vehicles that could be controlled by a single human operator. However, FO is inappropriate for systems with a lower level of automation where vehicles are remotely controlled by a human, such as RGCS. The theoretical background of the suggested framework is based on McRuer’s crossover model that was initially developed in the aviation domain for explaining pilot handling issues. In this study, an evaluation/analysis software prototype was developed, known as the RGCS operability evaluation tool in a simulated environment (ROPES). The ROPES was designed to be a simple tool for use by officers or researchers who only have intuitive understanding on the human adaptability. The ROPES includes two sub-modules; 1) an interactive interface for the configuration of the RGCS dynamic parameters and user interfaces and 2) a time-varying graphical display of system and human performance. Examples case studies demonstrate the advantage of the ROPES, and improvement points were identified for future development.     

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.     

Thermal Transport in Nanoporous Yttria-Stabilized Zirconia by Molecular Dynamics Simulation

Yttria-stabilized zirconia (YSZ) is widely used as thermal barrier coatings (TBCs) to reduce heat transfer between hot gases and metallic components in gas-turbine engines. Porous structure can generally reduce the lattice thermal conductivity of bulk material, so porous YSZ can be potentially used as TBCs with better thermal performance. In this work, we investigate the thermal conductivity of nanoporous YSZ using the nonequilibrium molecular dynamics (NEMD) simulation, and comprehensively discuss the effects of cross-sectional area, pore size, structure length, porosity, Y₂O₃ concentration and temperature on the thermal conductivity. To compare with the results of the NEMD simulation, we solve the heat diffusion equation and the gray Boltzmann transport equation (BTE) to calculate the thermal conductivity of the same porous structure. From the results, we find that the thermal conductivity of YSZ has a weak dependence on the structure length at the length range from 10 to 26 nm, which indicates that the majority of heat carriers have very short mean free path (MFP) but there exists small percentage (about 3%) of phonons with longer MFP (larger than 10 nm) contributing to the thermal conductivity. The thermal conductivity predicted by NEMD simulation is smaller than that of solving heat diffusion equation (diffusive limit) with the same porous structure. It shows that the presence of pores affects phonon scattering and further affects the thermal conductivity of nanoporous YSZ. The results agree well with the solution of gray BTE with a average MFP of 0.6 nm. The thermal conductivity of nanoporous YSZ weakly depends on the Y₂O₃ concentration and temperature, which shows the phonons with very short MFP play the major contribution to the thermal conductivity. The results help to better understand the heat transfer in porous YSZ structure and develop better TBCs.