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In this paper, the predictive control strategy is employed to improve the current tracking performance of hub motor in 4WD electric vehicle due to its fast dynamic response. But the performance of the conventional predictive deadbeat current control suffers greatly from the parameter variations and other disturbances. Toward this, this paper presents a new predictive control strategy for hub motor; this control scheme combines an improved predictive control law with a state-observer to estimate the future motor currents and system disturbances based on a decoupled model. It provides a decoupled control of hub motor and offers stability against the variations in motor inductance and robustness against system uncertainties. The feasibility and validity of the proposed predictive current control strategy is verified through the simulation results.

Four-wheel-drive electric vehicles (4WD Evs) utilize in-wheel electric motors and Electro-Hydraulic Braking system (EHB). Then, all wheels torque can be controlled independently, and the braking pressure can be controlled more accurately and more fast than conventional braking system. Because of these advantages, 4WD Evs have potential applications in control engineering. In this paper, the in-wheel electric motors and EHB are applied as actuators in the vehicle stability control system. Based on the Direct Yaw-moment Control (DYC), the optimized wheel force distribution is given, and the coordination control of the hydraulic braking and the motor braking torque is considered. Then the EHB hardware-in-the-loop test bench is established in order to verify the effectiveness of the vehicle stability control algorithm through experiments.

Pressure following control is the basic function of Electro-Hydraulic Braking system (EHB), which is also the key technology of stability control system and regenerative braking system for hybrid and electric vehicles. Experimental research is an important method for the control and application of EHB. This paper describes a method to test and control the EHB system through experiment on the Hardware-in-the-loop (HIL) test bench and wheel motor electric vehicle. First, the HIL test bench was established, in which the EHB was tested, including the characteristics of solenoid valves and motor. Then the wheel cylinder pressure was controlled to follow the specific signal input and the master cylinder pressure. Based on this, EHB and the pressure following control method were applied to the wheel motor electric vehicle. The results show that the braking pressure can follow the driver's braking intention to realize the conventional braking function of electric vehicles.

In this paper, a sliding mode observer for estimating vehicle slip angle and tire forces is developed. Firstly, the sliding mode observer design approach is presented. A system damping is included in the sliding mode observer to speed the observer convergence and to decrease the observer chattering. Secondly, the sliding mode observer for vehicle states is developed based on a 7 DOF embedded vehicle model with a nonlinear tire model ‘UniTire’. In addition, since the tire lateral stiffness is sensitive to the vertical load, the load transfers are considered in the embedded model with a set of algebraic equations. Finally, a simulation evaluation of the proposed sliding mode observer is conducted on a validated 14 DOF vehicle model. The simulation results show the model outputs closely match the estimations by the proposed sliding mode observer.

For high torque permanent magnet wheel motor, this paper describes an experimental research method to optimize and identify the motor parameters based on the results of offline calculation. In order to improve the accuracy of motor parameters identification, the motor model considering the affect of iron loss was established, and the motor parameters were identified using genetic algorithm (GA). Based on this, parameters validation experiment was performed. The results show that: parameters obtained by this method can be used to describe the steady-state and transient-state response of permanent magnet synchronous motors accurately.

Expansion chamber mufflers are commonly applied to reduce noise in HVAC. Dissipative materials, such as microperforated plates (MPPs), are often applied to achieve a more broadband mitigation effect. Such mufflers are typically characterized in the frequency domain, assuming time-harmonic excitation. From a computational point of view, transient analyses are more challenging. A transformation of the equivalent fluid model or impedance boundary conditions into the time domain induces convolution integrals. We apply the recently proposed finite element formulation of a time domain equivalent fluid (TDEF) model to simulate the transient response of dissipative acoustic media to arbitrary unsteady excitation. As most time domain approaches, the formulation relies on approximating the frequency-dependent equivalent fluid parameters by a sum of rational functions composed of real-valued or complex-conjugated poles.

When travelling in an open-jet wind tunnel, the path of an acoustic wave is affected by the flow causing a shift of source positions in acoustical maps of phased arrays outside the flow. The well-known approach of Amiet attempts to correct for this effect by computing travel times between microphones and map points based on the assumption that the boundary layer of the flow, the so-called shear-layer, is infinitely thin and refracts the acoustical ray in a conceptually analogy to optics. However, in reality, the turbulent nature of both the not-so thin shear-layer and the acoustic emission process itself causes an additional smearing of sources in acoustic maps, which in turn causes deconvolution methods based on these maps - the most prominent example being CLEAN-SC - to produce certain ring effects, so-called halos, around sources.

Although structural intensity was introduced in the 80's, this concept never found practical applications, neither for numerical nor experimental approaches. Quickly, it has been pointed out that only the irrotational component of the intensity offers an easy interpretation of the dynamic behavior of structures by visualizing the vibration energy flow. This is especially valuable at mid and high frequency where the structure response understanding can be challenging. A new methodolodgy is proposed in order to extract this irrotational intensity field from the Finite Element Model of assembled structures such as Bodies In White. This methodology is hybrid in the sense that it employs two distinct solvers: a dynamic solver to compute the structural dynamic response and a thermal solver to address a diffusion equation analogous to the thermal conduction built from the previous dynamic response.

Centrifugal fans are applied in many industrial and civil applications, such as manufacturing processes and building HVAC systems. They can also be found in automotive applications. Noise-reduction mea- sures for centrifugal fans are often challenging to establish, as acous- tic performance may be considered a tertiary purchase criterion after energetic efficiency and price. Nonetheless, their versatile application raises the demand for noise control. In a low-Mach-number centrifugal fan, acoustic waves are predominantly excited by aerodynamic fluctu- ations in the flow field and transmit to the exterior via the housing and duct walls. The scientific literature documents numerous mech- anisms that cause flow-induced sound generation, even though only some are considered well-understood. Numerical simulation methods are widely used to gather spatially high-resolved insights into physical fields.

The fuel permeation rate of elastomers is an important factor to consider in the design of automotive fuel system components. Evaporative hydrocarbon emission losses are now tightly regulated. The new 2 gram in 24 hour limit in a 20-40°C diurnal SHED test must be met not only when the car is built, but also at any time up to 10 years or 100,000 miles of service, or for trucks 11 years or 120,000 miles. The SHED test protocol calls for draining the fuel system on a car that has been in service and refilling with a non-oxygenated test fuel. However, the car may have been using an oxygenated fuel prior to the test. There has been speculation that the more permeable oxygenated fuel will influence the permeation rates through the elastomeric components for some time after the original oxygenated fuel has been drained from the vehicle.

The tire lateral force is essential to the vehicle handling and stability under cornering. However, it is difficult for engineers to get the tire lateral force under high loading condition due to the limitation of loading ability for most tire test machine in the world. The widely used semi-empirical tire lateral force models are obtained by curve-fitting experiments data and thus unable to predict the load dependent lateral force. The objective of this paper is to predict the tire lateral force under high-load condition based on the low-load tire data. The nonlinear characteristics of the tire cornering stiffness with the load are greatly affected by the tire carcass compliance. In this paper, a theoretical tire lateral model was built by considering carcass complex deformation. Combined with the relationship between the half-length of the tire contact patch and the load, the non-linear characteristics of the tire cornering stiffness with load were obtained.

With the development of the advanced driver assistance system and autonomous vehicle techniques, a precise description of the driver’s steering behavior with mathematical models has attracted a great attention. However, the driver’s steering maneuver demonstrates the stochastic characteristic due to a series of complex and uncertain factors, such as the weather, road, and driver’s physiological and psychological limits, generating negative effects on the performance of the vehicle or the driver assistance system. Hence, this paper explores the stochastic characteristic of driver’s steering behavior and a novel steering controller considering this stochastic characteristic is proposed based on stochastic model predictive control (SMPC). Firstly, a search algorithm is derived to describe the driver’s road preview behavior.

A long vehicle is more difficult to drive than a short one, but the mechanism of this phenomenon is still ambiguous. This paper will devote main effort to elaborate this phenomenon based on the theory of preview-follower driver model. Drivers always hope that the vehicle center can travel according to a predetermined trajectory. However, there is often a deviation between the vehicle center predicted by the driver and the actual center. As for this phenomenon, a conception of driver preview eccentricity is proposed. In order to analyze the influence of the proposed conception on vehicle driving track, a multi-axle steering vehicle model is built and some basic expressions of important parameters are deduced from this model firstly. Then, the developmental driver model with the factor of preview eccentricity based on preview-follower theory is established in the state of low velocity quasi-static. Subsequently, this model for long vehicles is extended to a dynamic driver model.

Plug-In Hybrid Vehicles (PHEV) have been of significant importance recently to comply with future CO2 and pollutant emissions limit. However, performance of these vehicles is closely related to the energy management strategy (EMS) used to ensure minimum fuel consumption and maximize electric driving range. While conventional EMS concepts are developed to operate in wide range of scenarios, this approach could potentially compromise the fuel consumption benefit due to the omission of route and traffic information. With the advancements in the availability of real-time traffic, navigation and driving route information, the EMS can be further optimized to extract the complete potential of a PHEV. In this context, this paper presents application of predictive energy management (PEM) functionalities combined with information such as live traffic data to reduce the fuel consumption for a P1/P3 configuration PHEV vehicle.

The aim of this study is to examine the effects of chemical treatments on the performance of composites that are reinforced with natural fibres. Natural fibres have several advantages, such as low density, low cost, and environmental friendliness, as they can be biodegraded or recycled. However, natural fibre composites also have some limitations, such as their poor compatibility with the matrix material and the reinforcement material. This leads to weak interfacial bonding and poor mechanical properties. Another problem with natural fibres is that they absorb more moisture than other materials, which can affect their dimensional stability and durability. Therefore, this research compares the compatibility of different chemical treatments that can modify the surface properties of natural fibres and improve their adhesion with the matrix and reinforcement.

The quality of the finished product depends on the contribution of many factors along with the complex process involved to move forward towards the new product development. Many operations like turning, drilling, milling in metal machining deserves the quality as a predominant measurement. The tool and work piece plays a vital role in machining process which depends on machining parameters such as spindle speed, feed rate, depth of cut, approach angle. In the present work the turning operation was carried out on Nickel alloy (Nimonic 80) as a work piece and the carbide insert was used as a tool for performing the machining operations. The cutting parameters were optimized using Taguchi based grey relational analysis. Provided that, the ANOVA analysis to find the predominant factors that affects the quality were also determined. The experimental results were compared with the predicted results and found to be a promising agreement between the factors and responses.

In the acoustic study of the interior noise of a vehicle, whether for structure-borne or air-borne excitations, knowing which areas contribute the most to interior noise and therefore should be treated as a priority, is the main goal of the engineer in charge of the NVH. Very often these areas are numerous, located in different regions of the vehicle and contribute at different frequencies to the overall sound pressure level. This has led to the development of several “Panel Contribution Analysis” (PCA) experimental techniques. For example, a well-known technique is the masking technique, which consists of applying a “maximum package” (i.e., a package with very high sound insulation) to the panels outside of the area whose contribution has to be measured. This technique is pragmatic but rather cumbersome to implement. In addition, it significantly modifies the dynamics and internal acoustics of the vehicle.

Electrified vehicles are particularly quiet, especially at low speeds due to the absence of combustion noises. This is why there are laws worldwide for artificial driving sounds to warn pedestrians. These sounds are generated using a so-called Acoustic Vehicle Alerting System (AVAS) which must maintain certain minimum sound pressure levels in specific frequency ranges at low speeds. The creation of the sound currently involves an iterative and sometimes time-consuming process that combines composing the sound on a computer with measuring the levels with a car on an outside noise test track. This continues until both the legal requirements and the subjective demands of vehicle manufacturers are met. To optimize this process and reduce the measurement effort on the outside noise test track, the goal is to replace the measurement with a simulation for a significant portion of the development.

Though modal analysis is a common tool to evaluate the dynamic properties of a structure, there are still many individual decisions to be made during the process which are often based on experience and make it difficult for occasional users to gain reliable and correct results. One of those experience-based choices is the correct number and placement of reference points. This decision is especially important, because it must be made right in the beginning of the process and a wrong choice is only noticeable in the very end of the process. Picking the wrong reference points could result in incomplete modal analysis outcomes, as it might make certain modes undetectable, compounded by the user's lack of awareness about these missing modes. In the paper an innovative approach will be presented to choose the minimal number of mandatory reference points and their placement.

In electrified vehicles, auxiliary units can be a dominant source of noise, one of which is the refrigerant scroll compressor. Compared to vehicles with combustion engines, e-vehicles require larger refrigerant compressors, as in addition to the interior, the battery and the electric motors must be cooled. The compressor causes the acoustic excitation of other refrigeration circuit components and the chassis via pressure pulsations and vibration transmission, as well as emitting airborne sound directly. Sound measurements have been performed in an anechoic chamber to investigate the influence of operating conditions on the acoustics of an electric scroll compressor. This paper investigates the influence of the operating conditions on compressor acoustics and shows that rotation speed is the main factor influencing compressor noise. The sound spectra of fluid, structure and airborne noise are dominated by speed-dependent, tonal components.