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Effectively obtaining physical parameters for vehicle dynamic model is the key to successfully performing any computer-based dynamic analysis, control strategy development or optimization. For a spring and lump mass vehicle model, which is a type of vehicle model widely used, its physical parameters include sprung mass, unsprung mass, inertial properties of the sprung mass, stiffness and damping coefficient of suspension and tire, etc. To minimize error, the paper proposes a method to estimate these parameters from vehicle modal parameters which are in turn obtained through full-car dynamic testing. To verify its effectiveness, a visual vehicle with a set of given parameters, build in the Adams(Automatic Dynamic Analysis of Mechanical Systems)/Car environment, is used to perform the dynamic testing and provide the testing data for the parameter estimation.

With the development of advanced ABE fermentation technology, the volumetric percentage of acetone, butanol and ethanol in the bio-solvents can be precisely controlled. To seek for an optimized volumetric ratio for ABE-diesel blends, the previous work in our team has experimentally investigated and analyzed the combustion features of ABE-diesel blends with different volumetric ratio (A: B: E: 6:3:1; 3:6:1; 0:10:0, vol. %) in a constant volume chamber. It was found that an increased amount of acetone would lead to a significant advancement of combustion phasing whereas butanol would compensate the advancing effect. Both spray dynamic and chemistry reaction dynamic are of great importance in explaining the unique combustion characteristic of ABE-diesel blend. In this study, a semi-detailed chemical mechanism is constructed and used to model ABE-diesel spray combustion in a constant volume chamber.

This paper intends to present a novel optimal trajectory planning method for obstacle avoidance on highways. Firstly, a mapping from the road Cartesian coordinate system to the road Frenet-based coordinate system is built, and the path lateral offset in the road Frenet-based coordinate system is represented by a function of quintic polynomial respecting the traveled distance along the road centerline. With different terminal conditions regarding its position, heading and curvature of the endpoint, and together with initial conditions of the starting point, the path planner generates a bunch of candidate paths via solving nonlinear equation sets numerically. A path selecting mechanism is further built which considers a normalized weighted sum of the path length, curvature, consistency with the previous path, as well as the road hazard risk.

Aerodynamic noise generated in a miniature car had been evaluated using numerical simulation. Large Eddy Simulation (LES) was applied to analyze the transient flow field and the Ffowcs Williams-Hawkings (FW-H) acoustic analogy was employed to conduct acoustic analysis. The time accurate flow data was obtained using a finite volume flow solver on an unstructured grid. The flow field around the rear view mirror was obtained by numerical for two cases with different side view mirrors. Moreover, the distribution of acoustic source was predicted on side windows, and the aerodynamic noise was lowed through optimizing the shape of the rear view mirror and some experiments were done to validate the effect. Present study ascertained the feasibility and applicability of finite volume method (FVM) with SGS model towards prediction of aerodynamic noise generated in production vehicle.

Optimization design for vehicle front-end structures has proven rather essential and been extensively used to improve the vehicle performance. Nevertheless, the front-end structure needs to meet the requirement of both pedestrian safety and structural stiffness which are somewhat contradicting to each other. Furthermore, an optimal design could become less meaningful or even unacceptable when some uncertainties present. In the paper, a multi-objective discrete robust optimization (MODRO) algorithm is used to minimize the injury of head and maximize the structural stiffness involving uncertainties. MODRO algorithm is achieved by coupling grey relational analysis (GRA) and principal component analysis (PCA) with Taguchi method. The optimized result shows that the MODRO algorithm improved performance of pedestrian head injury and robustness of the vehicle front-end structure.

A multidimensional numerical simulation method was developed to analyze air/fuel premixing, stratified combustion and NOx emission formation in a gasoline direct injection (GDI) engine. Firstly, many submodels were integrated into one Computational Fluid Dynamics (CFD) code: ICFD-CN, such as Sarre nozzle flow, Kelvin-Helmholtz (KH) dynamic jet model, Taylor-Analogy Breakup (TAB) model, Rayleigh-Taylor (RT) droplet breakup model, Lefebvre fuel vaporization model, Liu droplet drag & distortion model, Gosman turbulence & droplet dispersion model, O'rourke wall film model, O'rourke and Bracco droplet impinging & coalescence model, Stanton spray/wall impinging model, the Discrete Particle Ignition Kernel(DPIK)ignition model, the single step combustion and the patulous Zeldovich model for NOx generation mechanism. The integrated CFD code was then calibrated against experimental data in a gasoline direct injection engine for several engine operating conditions.

A hybrid approach utilizing the measured intake/exhaust port pressure traces and gas dynamics simulation was developed to process the instant fresh charge and RGF (Residual Gas Fraction) trapped in cylinder. The real time RGF, pumping losses and indicated thermal efficiency of an automotive gasoline engine under vehicle driving conditions are analyzed, cycle by cycle, and associated to the engine operating parameters including engine load, speed, VVT positions, manifold pressure and temperatures, as well as spark timing. In this way the inter-relationship among those parameters are established. The derived relationship could be used to determine the in-cylinder process for more accurate prediction of engine performance at the stage of concept simulation study, and applied to narrow the range of parameter tests in the engine calibration stage.

The traditional deterministic optimal design is mostly based on meeting regulatory requirements specified in impact standards, without taking the randomness of the impact velocity and angle at the real world situation into consideration. This often leads to the optimization results that converge to the boundary constraints, thus cannot meet the reliability requirements of the product design. Structure members of B-pillar (e.g. inner panel, outer panel, and the reinforcing plate) play a major role in the side impact safety performance. This paper dealt with optimization of B-pillar by considering its dimensions and materials as the design variables, and the impact velocity and angle from real-world traffic accident conditions as the random variable inputs. Using a combination of design of experiment, response surface models, reliability theory and the reliability of design optimization method, a B-pillar was constructed based on the product quality engineering.

Uncertainties present a large concern in actual vehicle motion and have a large effect on vehicle system control. We attempt a new robust control design approach for braking/driving force distribution and active front steering of vehicle system with uncertain parameters. The braking/driving force distribution control is equivalently studied as the integral direct yaw moment control. Then the control design is carried out by using a state-space vehicle model with embedded fuzzy uncertainties. By taking the compensated front wheel steering angle and the direct yaw moment as the control inputs, a feedback control that aims to compensate the system uncertainty is proposed. In a quite different angle, we employ fuzzy descriptions of the uncertain parameters. The controlled system performance is deterministic, and the control is not if-then rules-based. Fuzzy descriptions of the uncertain parameters are used to find an optimal control gain.

Realizable k-ε turbulence model has been used widely for engineering development. In this turbulence model, the default values of empirical coefficients such as C₂, σk and σε are obtained from some particular experiments. They are a good choice for most simulations-though may be not the best choice for simulating the aerodynamic characteristics of road vehicle. In order to improve the accuracy of simulation, a set of new empirical coefficients should be designed especially for simulating the aerodynamic characteristics of road vehicle. These empirical coefficients are found out by DoE (design of experiments) in this paper. Firstly the value range of empirical coefficients is decided by the laws that the aerodynamic force coefficients change with altering of empirical coefficients. Secondly 20 sets of empirical coefficients are obtained randomly by applying optimal Latin Hypercube method in Isight.

Good handling stability becomes very important for heavily-laden electric wheel dump trucks that are operated on rough roads. To improve handling stability of mining dump trucks, nonlinear stiffness and nonlinear damping of the hydro-pneumatic suspension were considered as optimization variables. In this paper, based on the Daubechies wavelet's compactness and regularization and least-square method, the nonlinear stiffness and damping are identified. In order to verify the results of the parameter identification, the multi-body system dynamic model of the truck was built in ADAMS/view. By comparing the simulated results and tested ones, we find acceleration-history and power spectral density of acceleration are very close. And then, based on the approximate model method, the optimization model was built in ISIGHT. The nitrogen column and the orifice diameter were defined as the design variables. Finally, the handling stability was optimized by applying the genetic algorithms method.

This paper presents an optimal cooperative path planning method considering driver’s driving intention for shared control to address target path conflicts during the driver-automation interaction by using the convex optimization technique based on the natural cubic spline. The optimal path criteria (e.g. the optimal curvature, the optimal heading angle) are formulated as quadratic forms using the natural cubic spline, and the initial cooperative path profiles of the cooperative path in the Frenet-based coordinate system are induced by considering the driver’s lane-changing intention recognized by the Support Vector Machine (SVM) method. Then, the optimal cooperative path could be obtained by the convex optimization techniques. The noncooperative game theory is adopted to model the driver-automation interaction in this shared control framework, where the Nash equilibrium solution is derived by the model predictive control (MPC) approach.

The around view monitor (AVM) system for the long-body road vehicle with multiple articulated carriages usually suffers from the incomplete distortion rectification of fisheye cameras and the irregular image stitching area caused by the change of relative position of the cameras on different carriages while the vehicle is in motion. In response to these problems, a set of calibration and stitching methods of AVM are proposed. First, a radial-distortion-based rectification method is adopted and improved. This method establishes two lost functions and solves the model parameters with the two-step optimization method. Then, AVM system calibration is conducted, and the perspective transformation matrix is calculated. After that, a static basic look-up table is generated based on the distortion rectification model and perspective transformation matrix.

Lightweight automotive body can be obtained by developing new body constructions, using lightweight materials and structural optimizations, etc. Usually, lighter materials and structural optimizations are main aspects considered in lightweight automotive body engineering. In fact, material costs and manufacturability play more important roles than others in lightweight design. Three lightweight design approaches are considered. The first approach of lightweight design is to replace steels with lighter materials using equal rigidity design method. The second approach is a single objective optimization of mass reduction with materials selection and cost penalty. The third approach is a multi-objective optimization of mass reduction and cost reduction using multi-material concept. These three approaches are applied to an automotive body design problem considering the side impact. Different optimization methods are used to obtain different results.

Hydraulic retarder, as an auxiliary braking device, is widely used in commercial vehicles. Nowadays, the hydraulic retarder’s internal oil is mainly cooled by the coolant circuit directly. It not only aggravates the load of engine cooling system, but also makes the abundant heat energy not be recycled properly. In this study, an independent energy supply device with organic Rankine cycles is applied to solve the problems above. In the structure of this energy supply device, the evaporator’s inlet and outlet is connected in parallel with the oil outlet and inlet of the retarder respectively. A part of oil enters the evaporator to transfer heat with the organic fluid, and the rest of oil enters the oil-water heat exchanger to be cooled by the coolant circuit. According to the different braking conditions of the retarder, the oil temperature in the inlet of the hydraulic retarder can be kept within the proper range through adjusting the oil flow rate into the evaporator properly.

The temperature monitoring of the lithium-ion battery is crucial for the advanced battery thermal management systems (BTMS) to improve performance and ensure operational safety and reliability of the battery system. In real applications, the core temperature of the battery is unfortunately unmeasurable due to the impracticality of placing a sensor inside the core, and has to be estimated online in real-time. Meanwhile, only the measurement of battery surface temperature can not meet the need for advanced BTMS due to the impact of the large temperature gradient between the surface and internal in high power applications. The battery core temperature estimation will become challenging when encountering sensor bias and noise.