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A control algorithm is developed for active/semi-active suspensions which can provide more comfort and better handling simultaneously. A weighting parameter is tuned online which is derived from two components - slow and fast adaptation to assign weights to comfort and handling. After establishing through simulations that the proposed adaptive control algorithm can demonstrate a performance better than some controllers in prior-art, it is implemented on an actual vehicle (Cadillac STS) which is equipped with MR dampers and several sensors. The vehicle is tested on smooth and rough roads and over speed bumps.

The analysis of nickel metal hydride (Ni-MH) battery performance is very important for automotive researchers and manufacturers. The performance of a battery can be described as a direct consequence of various chemical and physical phenomena taking place inside the container. In this paper, a physics-based model of a Ni-MH battery will be presented. To analyze its performance, the efficiency of the battery is chosen as the performance measure, which is defined as the ratio of the energy output from the battery and the energy input to the battery while charging. Parametric sensitivity analysis will be used to generate sensitivity information for the state variables of the model. The generated information will be used to showcase how sensitivity information can be used to identify unique model behavior and how it can be used to optimize the capacity of the battery. The results will be validated using a finite difference formulation.

As one of the most important auto-body moving parts, door hinge is the key point of door design and its accessories arrangement, also the premise of the door kinematic analysis. We proposed an effective layout procedure for door hinge and developed an intelligent system on CATIA CAA platform to execute it. One toolbar and five function modules are constructed - Axis Arrangement, Section, Parting Line, Kinematic, Hinge Database. This system integrated geometrical algorithms, automatically calculate the minimum clearances between doors, fender and hinges on sections to judge if the layout is feasible. As the sizes of the clearances are set to 0s, the feasible layout regions and extreme start/end points are shown in parts window, which help the engineer to check the parting line and design a new one. Our system successfully implemented the functions of five modules for the layout of door hinge axis and parting line based on a door hinge database.

Controlled Auto-Ignition (CAI) combustion can effectively improve the thermal efficiency of conventional spark ignition (SI) gasoline engines, due to shortened combustion processes caused by multi-point auto-ignition. However, its commercial application is limited by the difficulties in controlling ignition timing and violent heat release process at high loads. Stratified flame ignited (SFI) hybrid combustion, a concept in which rich mixture around spark plug is consumed by flame propagation after spark ignition and the unburned lean mixture closing to cylinder wall auto-ignites in the increasing in-cylinder temperature during flame propagation, was proposed to overcome these challenges.

Engine knock is an abnormal phenomenon, which places barriers for modern Spark-Ignition (SI) engines to achieve higher thermal efficiency and better performance. In order to trigger more controllable knock events for study while keeping the knock intensity at restricted range, various spark strategies (e.g. spark timing, spark number, spark location) are applied to investigate on their influences on knock combustion characteristics and pressure oscillations. The experiment is implemented on a modified single cylinder Compression-Ignition (CI) engine operated at SI mode with port fuel injection (PFI). A specialized liner with 4 side spark plugs and 4 pressure sensors is used to generate various flame propagation processes, which leads to different auto-ignition onsets and knock development. Based on multiple channels of pressure signals, a band-pass filter is applied to obtain the pressure oscillations with respect to different spark strategies.

The performance, life cycle cost, and safety of electric and hybrid electric vehicles (EVs and HEVs) depend strongly on their energy storage system. Advanced batteries such as lithium-ion (Li-ion) polymer batteries are quite viable options for storing energy in EVs and HEVs. In addition, thermal management is essential for achieving the desired performance and life cycle from a particular battery. Therefore, to design a thermal management system, a designer must study the thermal characteristics of batteries. The thermal characteristics that are needed include the surface temperature distribution, heat flux, and the heat generation from batteries under various charge/discharge profiles. Therefore, in the first part of the research, surface temperature distribution from a lithium-ion pouch cell (20Ah capacity) is studied under different discharge rates of 1C, 2C, 3C, and 4C.

In this paper, a consensus framework for cooperative parameter estimation within the vehicular network is presented. It is assumed that each vehicle is equipped with a dedicated short range communication (DSRC) device and connected to other vehicles. The improvement achieved by the consensus for parameter estimation in presence of sensor’s noise is studied, and the effects of network nodes and edges on the consensus performance is discussed. Finally, the simulation results of the introduced cooperative estimation algorithm for estimation of the unknown parameter of road condition is presented. It is shown that due to the faster dynamic of network communication, single agents’ estimation converges to the least square approximation of the unknown parameter properly.

System identification is an important aspect in model-based control design which is proven to be a cost-effective and time saving approach to improve the performance of hybrid electric vehicles (HEVs). This study focuses on modeling and parameter estimation of the longitudinal vehicle dynamics for Toyota Prius Plug-in Hybrid (PHEV) with power-split architecture. This model is needed to develop and evaluate various controllers, such as energy management system, adaptive cruise control, traction and driveline oscillation control. Particular emphasis is given to the driveline oscillations caused due to low damping present in PHEVs by incorporating flexibility in the half shaft and time lag in the tire model.

Forecasting the motion of the leading vehicle is a critical task for connected autonomous vehicles as it provides an efficient way to model the leading-following vehicle behavior and analyze the interactions. In this study, a personalized time-series modeling approach for leading vehicle trajectory prediction considering different driving styles is proposed. The method enables a precise, personalized trajectory prediction for leading vehicles with limited inter-vehicle communication signals, such as vehicle speed, acceleration, space headway, and time headway of the front vehicles. Based on the learning nature of human beings that a human always tries to solve problems based on grouping and similar experience, three different driving styles are first recognized based on an unsupervised clustering with a Gaussian Mixture Model (GMM).

A new power control unit (PCU) has been developed for a Honda small hybrid vehicle with a two-motor hybrid system launched in 2020. For small hybrid vehicles, downsizing and reducing costs of hybrid systems are major challenges. As such, there were emphatic requirements for the newly developed PCU to be small and affordable. To satisfy these requirements for the PCU, new technologies and components have been introduced such as an all-in-one type intelligent power module (IPM) with integrated functions and reverse conducting IGBT (RC-IGBT), a new control sequence for voltage control unit (VCU), and revised PCU packaging to improve cooling performance. The new IPM has a printed-circuit board (PCB) equipped with an electric control unit (ECU) and gate drive circuits, 7 current sensors, and a power module with RC-IGBTs. This functional integration led to a reduction in the number of main electrical PCU assembly components from 9 in the previous PCU to 2 in the new PCU.

This work numerically investigates the detailed combustion kinetics of partially premixed combustion (PPC) in a diesel engine under three different premixed ratio fuel conditions. A reduced Primary Reference Fuel (PRF) chemical kinetics mechanism was coupled with CONVERGE-SAGE CFD model to predict PPC combustion under various operating conditions. The experimental results showed that the increase of premixed ratio (PR) fuel resulted in advanced combustion phasing. To provide insight into the effects of PR on ignition delay time and key reaction pathways, a post-process tool was used. The ignition delay time is related to the formation of hydroxyl (OH). Thus, the validated Converge CFD code with the PRF chemistry and the post-process tool was applied to investigate how PR change the formation of OH during the low-to high-temperature reaction transition. The reaction pathway analyses of the formations of OH before ignition time were investigated.

Strategies to suppress knock have been extensively investigated to pursue thermal efficiency limits in downsized engines with a direct-injection spark ignition. Comprehensive considerations were given in this work, including the effects of second injection timing and injector location on knock combustion in a downsized gasoline engine by large eddy simulation. The turbulent flame propagation is determined by an improved G-equation turbulent combustion model, and the detailed chemistry mechanism of a primary reference fuel is employed to observe the detailed reaction process in the end-gas auto-ignition process. The conclusions were obtained by comparing the data to the baseline single-injection case with moderate knock intensity. Results reveal that for both arrangements of injectors, turbulence intensity is improved as the injecting timing is retarded, increasing the flame propagation speed.

The purpose of this study is to investigate the spray characteristics and ignition stability of gasoline sprays injected from a hole-type nozzle. Using a single-hole VCO (Valve-Covered-Orifice) nozzle, the spray characteristics were studied with LAS (Laser Absorption Scattering) technique, and then flame propagation and ignition stability were investigated inside a high temperature high pressure constant volume vessel using a high speed video camera. The spatial ignition stability of the spray at different locations was tested by adjusting the position of the electrodes. By adjusting the ignition timings, the stable ignition windows for 3 determined locations where the ignition stability was high at a fixed ignition timing were studied. The flame propagation process was examined using high speed shadowgraph method. Experimental results show that when the ignition points are located on the spray axis, the ignition probability is low.

Aiming at the problem of poor robustness after the combination of lateral kinematics control and lateral dynamics control when an autonomous vehicle decelerates and changes lanes to overtake at a certain distance. This paper proposes a trajectory determination and tracking control method based on a PI-MPC dual algorithm controller. To describe the longitudinal deceleration that satisfies the lateral acceleration limit during a certain distance of lane change, firstly, a fifth-order polynomial and a uniform deceleration motion formula are established to express the lateral and longitudinal displacements, and a model prediction controller (MPC) is used to output the front wheel rotation angle. Through the dynamic formula and the speed proportional-integral (PI) controller to control and adjust the brake pressure.

As a major power source, diesel engines are being widely used in a variety of fields. However, because of complex structure, some faults which cannot be detected by direct signals would occur on engines and even lead to accidents. Among all kinds of indirect signals, vibration signal is the most common choice for faults detection without disassemble because of its convenience and stability. This paper proposed a novel approach for detecting multiple engine faults based on block vibration signals using variational mode decomposition (VMD) and echo state network (ESN). Since the quadratic penalty has a great influence on adaptable VMD that may make expected component signals cannot be extracted exactly, this paper proposed a dynamic quadratic penalty value, which will change with decomposing level. This paper selected a best dynamic quadratic penalty value by analyzing a large amount of data and results showed that this approach can decompose signals more exactly.

The non-conventional diesel nozzles have attracted more and more attention for their ability to promote jet breakup. In the present study, the internal nozzle flow and jet breakup relying on the convergent-divergent nozzle are investigated by combining the cavitation model and LES model with Multi-Fluid-Quasi-VOF model based on the OpenFOAM code. This is a novel method for which the interphase forces caused by the relative velocity of gas and liquid can be taken into account while sharpening the gas-liquid interface, which is able to accurately present the evolution processes of cavitation and jet breakup. Primarily, the numerical model was verified by the mass flow rate, spray momentum flux, discharge coefficient and effective jet velocity of the prototype Spray D nozzle from the literature.

It is imperative to have accurate tire models when trying to control the trajectory of a vehicle. With the emergence of autonomous vehicles, it is more important than ever before to have models that predict how the vehicle will operate in any situation. Many different types of tire models have been developed and validated, including physics-based models such as brush models, black box models, finite element-based models, and empirical models driven by data such as the Magic Formula model. The latter is widely acknowledged to be one of the most accurate tire models available; however, collecting data for this model is not an easy task. Collecting data is often accomplished through rigorous testing in a dedicated facility. This is a long and expensive procedure which generally destroys many tires before a comprehensive data set is acquired. Using a Vehicle Measurement System (VMS), tires can be modeled through on-road data alone.

Transparent materials such as Plexiglas and glass are applied in airplane and boat widely as the windows and hatches. There are three type stresses in the structure made of Plexiglas or glass, which are residual stresses from the casting, residual stresses due to manufacturing process involving sheet forming structure and the stresses from serving period. In the paper the stresses are studied by laser scattered Photoelasticy method. Phase shift method is presented to recognize scattered light patterns automatically. The residual stresses in Plexiglas plate and shell were analyzed by thin plate-shell theory. Stresses in the Plexiglas and shell were tested by laser scattered Photoelastic method.

In this study, a finite element software application (SORPAS®) is used to simulate the effect of pulsing on the expected weld thermal cycle during resistance spot welding (RSW). The predicted local cooling rates are used in combination with experimental observation to study the effect pulsing has on the microstructure and mechanical properties of Zn-coated DP600 AHSS (1.2mm thick) spot welds. Experimental observation of the weld microstructure was obtained by metallographic procedures and mechanical properties were determined by tensile shear testing. Microstructural changes in the weld metal and heat affect zone (HAZ) were characterized with respect to process parameters.

The increasingly stringent requirements in relation to emission reduction and onboard diagnostics are pushing the Chinese automotive industry toward more innovative solutions and a rapid increase in electronic control performance. To manage the system complexity the architecture will require being well structure on hardware and software level. The paper introduces GEMS-K1 (Gasoline Engine Management System - Kit 1). GEMS-K1 is a platform being compliant with Euro IV emission regulation for gasoline engines. The application software is developed using modeling language, the code is automatically generated from the model. The driver software has a well defined structure including microcontroller abstraction layer and ECU abstraction layer. The hardware is following design rules to be robust, 100% testable and easy to manufacture. The electronic components use the latest innovation in terms of architecture and technologies.