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Active safety and (ADAS) are now being introduced to the marketplace as they serve as key enablers for anticipated autonomous driving systems. Automatic emergency braking (AEB) is one ADAS application which is either in the marketplace presently or under development as nearly all automakers have pledged to offer this technology by the year 2022. This one-day course is designed to provide an overview of the typical ADAS AEB system from multiple perspectives.

This course applies advanced theory, physical tests and CAE to the assessment of ride, braking, steering and handling performance, governing state-space equations with transfer functions for primary ride and develop and analyze open loop handling. Building on the analysis of the state space equations, common physical tests and their corresponding CAE solutions for steady state and transient vehicle events.  The "state-of-the-art"  vehicle dynamics CAE, and common lab and vehicle tests with metrics used to assess chassis system and vehicle performance will be discussed.

Take notes! Take the wheel! There is no better place to gain an appreciation for vehicle dynamics than from the driver’s seat. Spend three, intense days with a world-renowned vehicle dynamics engineer and SAE Master Instructor, his team of experienced industry engineers, and the BMW-trained professional driving instructors. They will guide you as you work your way through 12 classroom modules learning how and why vehicles go, stop and turn. Each classroom module is immediately followed by an engaging driving exercise on BMW’s private test track.

This course will present an introduction to vehicle dynamics from a vehicle system perspective. The theory and applications are associated with the interaction and performance balance between the powertrain, brakes, steering, suspensions and wheel and tire vehicle subsystems.  The role that vehicle dynamics can and should play in effective automotive chassis development and the information and technology flow from vehicle system to subsystem to piece-part is integrated into the presentation. Governing equations of motion are developed and solved for both steady and transient conditions.

To investigate the rollover phenomena experienced by all-terrain vehicles (ATVs) during their motion caused by input from the road surface, a combined simulation using CarSim and Simulink has been employed to validate an active anti-rollover control strategy based on differential braking for ATVs, followed by vehicle testing. In the research process, a nonlinear three-degrees-of-freedom vehicle model has been developed. By utilizing a zero-moment point index as a rollover warning indicator, this approach could accurately detect the rollover status of the vehicle, particularly in scenarios involving low road adhesion on unpaved surfaces, which are characteristic of ATV operation. The differential braking, generating a roll moment by adjusting the amount of lateral force each braked tire can generate, was proved as an effective method to enhance rolling stability.

Abstract This article focuses on the development of an active braking control system tailored for electric vehicles. The essence of this system lies in its ability to regulate the slip coefficient to optimize traction during braking, thereby maximizing energy recuperation. In the context of the simulation on enhancing regenerative energy capture in electric vehicles, the use of integral sliding mode control (ISMC) as an alternative for regulating braking performance can be understood through a comparison of two key output variables in braking control systems: wheel deceleration and wheel slip. Traditionally, wheel deceleration has been a controlled variable in braking systems, and it is still utilized in some anti-lock braking systems (ABS). It can be easily measured using a basic wheel encoder. However, the dynamic performance of wheel deceleration control may suffer when there are rapid changes in the road surface.

The analysis presented in this document demonstrates the mathematical model approach for determining the rotation of a door about the hinge axis. Additional results from the model are the torque due to gravity about the axis, opening force, and the door hold open check link force. Vector mechanics, equations of a plane, and parametric equations were utilized to develop this model, which only requires coordinate points as inputs. This model allows for various hinge axis angles and door rotation angles to quickly be analyzed. Vehicle pitch and roll angles may also be input along with door mass to determine the torque about the hinge axis. The vector calculations to determine the moment arm of the door check link and its resulting force are demonstrated for both a standard check link design and an alternate check link design that has the link connected to a slider translated along a shaft.

Abstract In order to efficiently predict and investigate a vehicle’s vertical dynamics, it is necessary to consider the suspension component properties holistically. Although the effects of suspension stiffness and damping characteristics on vertical dynamics are widely understood, the impact of suspension friction in various driving scenarios has rarely been studied in both simulation and road tests for several decades. The present study addresses this issue by performing driving tests using a special device that allows a modification of the shock absorber or damper friction, and thus the suspension friction to be modified independently of other suspension parameters. Initially, its correct functioning is verified on a shock absorber test rig. A calibration and application routine is established in order to assign definite additional friction forces at high reproducibility levels.

In contemporary trajectory planning research, it is common to rely on point-mass model for trajectory planning. However, this often leads to the generation of trajectories that do not adhere to the vehicle dynamics, thereby increasing the complexity of trajectory tracking control. This paper proposes a local trajectory planning algorithm that combines sampling and sequential quadratic optimization, considering the vehicle dynamics model. Initially, the vehicle trajectory is characterized by utilizing vehicle dynamic control variables, including the front wheel angle and the longitudinal speed. Next, a cluster of sampling points for the anticipated point corresponding to the current vehicle position is obtained through a sampling algorithm based on the vehicle's current state. Then, the trajectory planning problem between these two points is modeled as a sequential quadratic optimization problem.

Intelligent tyres can offer crucial insights into tyre dynamics, serving as a fundamental information source for vehicle state estimation and thereby enabling vehicular safety control. Among the numerous tyre parameters, slip ratio stands out as a direct influencer of vehicle motion characteristics. Accurate estimation of tyre slip ratio is essential for vehicle safety. Firstly, an analysis of the fundamental composition of tyres was conducted, and appropriate simplifications were applied to the tyre structure. Additionally, a finite element model of the tyre was constructed using ABAQUS software. To validate the reliability of the model, a real vehicle testing system was established, consisting of the experimental vehicle, data acquisition system, and supervisory computer. The reliability of the finite element model was confirmed by assessing the consistency of acceleration signals in three different directions of the tyre.

As the main power source of new energy vehicles, the durability and fatigue characteristics of the battery pack directly affect the performance of the vehicle. The battery pack system was modelled using multi-body dynamics software, with 7 and 13 degree of freedom models developed. Using the established model, the intrinsic properties of the battery pack are computationally analyzed. To calculate the dynamic characteristics, a sinusoidal displacement excitation is applied to the wheel centre of mass, and the displacement and acceleration of the battery pack centre of mass are calculated for both models.The displacement and acceleration curves at the centre of mass of the battery pack of the two models are compared. The results show that the amplitude of the displacement and acceleration curves at the centre of mass of the 13 degrees of freedom model of the battery pack has decreased significantly.

This paper presents a torque distribution strategy for four-wheel independent drive electric vehicles (4WIDEVs) to achieve both handling stability and energy efficiency. The strategy is based on the dynamic adjustment of two optimization objectives. Firstly, a 2DOF vehicle model is employed to define the stability control objective for Direct Yaw moment Control (DYC). The upper-layer controller, designed using Linear Quadratic Regulator (LQR), is responsible for tracking the target yaw rate and target sideslip angle. Secondly, the lower-layer torque distribution strategy is established by optimizing the tire load rate and motor energy consumption for dynamic adjustment. To regulate the weights of the optimization targets, stability and energy efficiency allocation coefficient is introduced. Simulation results of double lane change and split μ road conditions are used to demonstrate the effectiveness of the proposed DYC controller.

With the development of hardware and control theory, the application of quadcopters is constantly expanding. Quadcopters have emerged in many fields, including transportation, exploration, and object grabbing and placement. These application scenarios require accurate, stable, and rapid control, and a suitable dynamic model is one of the prerequisites. At present, many works are related to it, most of which are modeled using the Newton-Euler method. Some works have also adopted other methods, including the Lagrangian and Hamiltonian methods. This article proposes a new method that solves the Hamiltonian equation of a quadcopter expressed in quasi-coordinate. The external forces and motion of the body are expressed in the quasi-coordinate system of the body, and solved through the Hamiltonian equation. This method simplifies operations and improves computational efficiency. Additionally, a single pendulum is attached to the quadcopter to simulate application scenarios.

The global energy crisis and drastic climate change are continuously promoting the implementation of sustainable energy sources. To meet the emission standards and carbon-neutrality targets in vehicle industry, ammonia is considered to be one of the promising carbon-neutral fuels. However, running the engines on high amounts of ammonia may lead to significantly high ammonia slip. This originates huge safety concerns. Therefore, hydrogen is added in certain ratio with ammonia to promote combustion and reduce ammonia slip. Furthermore, adding diesel as a pilot fuel further facilitates the combustion reactions. This experimental study investigated the effect of different ammonia-hydrogen blend ratios on in-cylinder pressure, heat release rate, cumulative heat release, indicated mean effective pressure (IMEP), indicated thermal efficiency (ITE), CA5 and CA50. This effect of blend ratios was tested for varied diesel pilot amounts and timings.

This paper demonstrates a data-driven methodology for the system-level design of high-power traction motor drives in modern battery electric vehicles. With the immense growth of battery electric vehicles in this transformative decade, the expected time to develop and market these powertrain components is becoming significantly shorter than for internal combustion engines. This rising demand is further complicated due to more stringent cost, efficiency and power density targets set by the U.S. Department of Energy. Hence, a system-level perspective is maintained in this data-driven methodology to identify the design requirements for traction motor drives by relying on a dynamic vehicle simulation toolchain and various drive cycles (e.g., EPA MCT, WLTC, US06, etc.). The proposed data-driven approach can be used across different battery electric vehicle platforms including passenger and commercial types.

Water removal from Proton Exchange Membrane (PEM) Fuel Cell (FC) mainly involves two phenomena: some of the emerging droplets will roll on the Gas Diffusion Layer (GDL), others may impact channel walls and start sliding along the airflow direction. This different behaviour is linked to the hydrophobic/hydrophilic nature of the surface the water is moving on. In this paper, the walls of the channel of a FC were characterized by applying optical techniques. The deposition of droplets on the channel wall led to an evaluation of the proper range for Contact Angle Hysteresis (CAH = 55° - 45°), and due to the high wettability of the surface, droplets dimension was defined with a dimensionless parameter B/H. Under high crossflow condition (15 m/s) a sliding behaviour was observed. The channel features determined through image processing were used as boundary conditions for a 2D CFD two phase simulation employing the Volume of Fluid (VOF) model to keep track of the fluids interface.

The paper introduces two methods for controlling motor voltage. One method requires the implementation of boost hardware, while the other allows for voltage control in battery failure mode without any additional hardware requirements. The boost voltage strategy for the hybrid system is based on managing boost modes, determining target voltages, and implementing PI control. The boost mode control includes different modes such as initial mode, normal mode, shutdown mode, and fault mode. Determining the boost target voltage involves regulating the boost converter with variable voltages depending on the operating states of the motor and generator. The second voltage control method without boost hardware is proposed in order to ensure that the vehicle can still function like a traditional car even under abnormal conditions of high-voltage battery failure in micro-mixing systems.

A need to develop a cooling method with high cooling performance like jet impingement is increased as high power of an inverter is required. Jet Impingement on the dimpled plate would increase thermal performance than that of flat plate. Many previous researchers have dealt with the multi jet impingement on flat plate and some results of the study on dimpled plate evaluate the effect on heat transfer coefficients on several limited cases, making it difficult to apply them to inverter designs. Therefore, in this paper, heat transfer performance, pressure drop, and robustness at micro-scale of jet impingement on the dimpled plate were investigated in detail and the correlations of each performance were proposed. Finally, the optimal design was presented. The cooling performance was influenced by the jet array and the effect of depth and width of the dimples.

Vibration from a mechanical system not only produces unwanted noises annoying to people around, but also runs a risk of fatigue failure that would actually hinder its functionality. There are several forms of vibration depending on the sources of excitation forms. Mechanical systems with rotating components can be subjected to sinusoidal excitation due to the fact the center of mass is not perfectly aligned with the rotating axis. If the rotating speed is strictly ramping up or ramping down, this can create an excitation whose frequency is changing with time in a frequency range corresponding to the speeds swept. Compared with a single sinusoidal excitation, the issue with fatigue at swept sinusoidal excitation, is that as it sweeps through a wide frequency range, some swept frequencies will definitely coincide with the natural frequencies of the system. Certainly, the stress response exactly at the resonant frequency becomes the highest and could account for a lot of fatigue damage.