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A method to improve the computational efficiency of analyzing wheeled vehicle systems on three-dimensional (3-D) roads has been developed. This was accomplished by creating a technique to incorporate the tire on a 3-D road in a multibody dynamics model of the vehicle with an approach that formulates the governing equations using symbolic formulation. For general handling analysis performed on the vehicle, the tire forces and moments are determined using a tire model that represents the tire as a set of mathematical expressions. Since these expressions need numerical values to determine the forces and moments, a symbolic solution does not exist. Therefore, the evaluation of the tire forces and moments needs to be done during simulation. However, symbolic operations can be used when the governing equations are formulated to develop an efficient method to evaluate these forces.

A simulation technology has been developed to enable prediction of galvanic corrosion in chassis parts where two different materials, iron and aluminum, come into contact with each other. When polarization curves representing a corrosive environment are input, this simulation technology calculates the corrosion current to flow and outputs the volume of aluminum corrosion to be formed near the iron-aluminum interface. The simulation makes it possible to predict the depth of corrosion that may occur in automobiles in the market.

Hole expansion of a dual phase steel, DP600, was numerically investigated using a damage-based constitutive law to predict failure. The parameters governing void nucleation and coalescence were identified from an extensive review of the x-ray micro-tomography data available in the literature to ensure physically-sound predictions of damage evolution. A recently proposed technique to experimentally quantify work-hardening and damage in the shear-affected zone is incorporated into the damage model to enable fracture predictions of holes with sheared edges. Finite-element simulations of a hole expansion test with a conical punch were performed for both a punched and milled hole edge condition and the predicted hole expansion ratios are in very good agreement with the experiment values reported by several researchers.

Small crack growth from notches under variable amplitude loading requires that crack opening stress be followed on a cycle by cycle basis and taken into account in making fatigue life predictions. The use of constant amplitude fatigue life data that ignores changes in crack opening stress due to high stress overloads in variable amplitude fatigue leads to non-conservative fatigue life predictions. Similarly fatigue life predictions based on small crack growth calculations for cracks growing from flaws in notches are non-conservative when constant amplitude crack growth data are used. These non-conservative predictions have, in both cases, been shown to be due to severe reductions in fatigue crack closure arising from large (overload or underload) cycles in a typical service load history.

In order to provide efficient thermal management for an electric vehicle, the development of the cooling and conditioning system has to start early on in the overall product development cycle. This means that the first simulation models have to make do with relatively few actual data, mostly based on concepts and design studies. Accordingly the possible results are mainly useable for early on feasibility assessments. With more data and more details available, these simulation models gradually evolve, until in the end the overall cooling system is modeled with a relatively high level of detail. This allows e.g. transient analysis of warm-up or cool-down runs, simulation of driving cycles, implementation and optimization of control strategies. Although this basic workflow is true both for ICE and electric vehicles, for the latter specific topics like battery thermal management and HVAC integration add to the overall complexity.

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.

Honda has developed an “Independent Left and Right Rear Toe Control System” that can achieve stable cornering performance and agile handling. We believe the issue that should be resolved in the next generation of ESC is the expansion of stability and agility into the general operation area. We examined how to accomplish this aim, and control of the independent rear toe angle was decided to be an appropriate method. In addition, a method for mounting the system without using a dedicated suspension was proposed. If left and right toe angles can be controlled independently, toe angle control and normal 4WS control become possible at the same time. In this paper, we will discuss the fundamental principle of independent toe angle control and the system configuration. Also, “INOMAMA Handling” (at driver's will) achieved by this system, as well as the fun and safe driving that are achieved as a result will be shown.

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.

In this research, a three degree-of-freedom (DOF) rack-type electric-based power steering (EPS) model is developed. The model is coupled with a three DOF vehicle model and includes EPS maps as well as non-linear attributes such as vibration and friction characteristics of the steering system. The model is simulated using Matlab's Simulink. The vibration levels are quantified using on-vehicle straight-line test data where strain-gauge transducers are placed in the tie-rod ends. Full vehicle kinematic and compliance tests are used to verify the total steering system stiffness levels. Frequency response tests are used to adjust tire cornering stiffness levels as well as the tire dynamic characteristics such that vehicle static gain and yaw natural frequency are achieved. On-center discrete sinusoidal on-vehicle tests are used to further validate the model.

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.

Recently vehicle development timeline is becoming shorter, so there is an urgent need to be able to develop vehicles with limited resources. This means the efficiency of the body structure development process must be improved. Specifically it is important to reduce the amount of design re-work required to meet performance targets as this can have a large influence on the body development time. In order to reduce the afore mentioned design re-work, we developed simple calculation models to apply a “V-Flow Development Process” to the preliminary stage design of the automobile body structure. The “V-Flow” advantages are as follows: (1) simple and easy to use, (2) defects are found at early stage, (3) avoids the downward flow of the defects. The advantage of preliminary stage design is that there is design flexibility since not many specifications have been determined yet.

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.

Energy management strategies greatly influence the power performance and fuel economy of series hybrid electric tracked bulldozers. In this paper, we present a procedure for the design of a power management strategy by defining a cost function, in this case, the minimization of the vehicle’s fuel consumption over a driving cycle. To explore the fuel-saving potential of a series hybrid electric tracked bulldozer, a dynamic programming (DP) algorithm is utilized to determine the optimal control actions for a series hybrid powertrain, and this can be the benchmark for the assessment of other control strategies. The results from comparing the DP strategy and the rule-based control strategy indicate that this procedure results in approximately a 7% improvement in fuel economy.

The interactions between automatic controls, physics, and driver is an important step towards highly automated driving. This study investigates the dynamical interactions between human-selected driving modes, vehicle controller and physical plant parameters, to determine how to optimally adapt powertrain control to different human-like driving requirements. A cyber-physical system (CPS) based framework is proposed for co-design optimization of the physical plant parameters and controller variables for an electric powertrain, in view of vehicle’s dynamic performance, ride comfort, and energy efficiency under different driving modes. System structure, performance requirements and constraints, optimization goals and methodology are investigated. Intelligent powertrain control algorithms are synthesized for three driving modes, namely sport, eco, and normal modes, with appropriate protocol selections. The performance exploration methodology is presented.

The development and calibration of stress state-dependent failure criteria for advanced high-strength steel (AHSS) and aluminum alloys requires characterization under proportional loading conditions. Traditional tests to construct a forming limit diagram (FLD), such as Marciniak or Nakazima tests, are based upon identifying the onset of strain localization or a tensile instability (neck). However, the onset of localization is strongly dependent on the through-thickness strain gradient that can delay or suppress the formation of a tensile instability so that cracking may occur before localization. As a result, the material fracture limit becomes the effective forming limit in deformation modes with severe through-thickness strain gradients, and this is not considered in the traditional FLD. In this study, a novel bending test apparatus was developed based upon the VDA 238-100 specification to characterize fracture in plane strain bending using digital image correlation (DIC).

This study developed technology for simultaneously welding heterogeneous resin tubes in order to weld and integrate resin tubes with two different specifications (low temperature and high temperature). The aim of integration was cost and weight reduction. The cost reduction due to reducing the number of parts exceeded the increase in material cost due to a change to resin materials. Base material fracture of the resin tubes was set as the breaking format condition, and the welding parameters of the joint part rotations and the friction time between the joint part and the resin tubes were specified as the weld strength judgment standard. In addition, the fused thickness determined by observing the cross-section after welding was specified as the weld quality judgment standard. The range over which weld boundary peeling does not occur and weld strength is manifest was clarified by controlling the welding parameters and the fused thickness.

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).

The SAE Fuel Cell Vehicle (FCV) Safety Working Group has been addressing FCV safety for over 9 years. The initial document, SAE J2578, was published in 2002. SAE J2578 has been valuable as a Recommended Practice for FCV development with regard to the identification of hazards and the definition of countermeasures to mitigate these hazards such that FCVs can be operated in the same manner as conventional gasoline internal combustion engine (ICE)-powered vehicles. SAE J2578 is currently being revised so that it will continue to be relevant as FCV development moves forward. For example, test methods were refined to verify the acceptability of hydrogen discharges when parking in residential garages and commercial structures and after crash tests prescribed by government regulation, and electrical requirements were updated to reflect the complexities of modern electrical circuits which interconnect both AC and DC circuits to improve efficiency and reduce cost.

The vision for the future automotive chassis is to interconnect the lateral, longitudinal, and vertical dynamics by separately controlling driving, braking, steering, and damping of each individual wheel. A major advantage of all wheel drive electric vehicles with four in-wheel motors is the possibility to control the torque and speed at each wheel independently. This paper proposes a traction controller for such a vehicle. It estimates the road's adhesion potential at each wheel and adjusts each motor voltage, such that the longitudinal slip is kept in an optimal range. For development and validation, a full vehicle model is designed in ADAMS/View software, in co-simulation with motor and control elements, modeled in MATLAB/Simulink.