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In this paper, a new computational method is provided to identify the uncertain parameters of Load Sensing Proportional Valve (LSPV) in a heavy truck brake system by using the polynomial chaos theory. The simulation model of LSPV is built in the software AMESim depending on structure of the valve, and the estimation process is implemented relying on the experimental measurements by pneumatic bench test. With the polynomial chaos expansion carried out by collocation method, the output observation function of the nonlinear pneumatic model can be transformed into a linear and time-invariant form, and the general recursive functions based on Newton method can therefore be reformulated to fit for the computer programming and calculation. To improve the estimation accuracy, the Newton method is modified with reference to Simulated Annealing algorithm by introducing the Metropolis Principle to control the fluctuation during the estimation process and escape from the local minima.

In this paper, a multi-mode active seat suspension with a single actuator is proposed and built. A one-DOF seat suspension system is modelled based on a quarter car model of commercial vehicle with an actuator which is comprised of a DC motor and a gear reducer. Aiming at improving ride comfort and reducing energy consumption, a multi-mode controller is established. According to the seat vertical acceleration and suspension dynamic travel signals, control strategies switch between three modes: active drive mode, energy harvesting mode and plug breaking mode.

Tyre behavior plays an important role in vehicle dynamics simulation. The Magic Formula Tyre Model is a semi-empirical tyre model which describes tyre behavior quite accurately in the handling simulation. The Magic Formula Tyre Model needs a set of parameters to describe the tyre properties; the determination of these parameters is nontrivial task due to its nonlinear nature and the presence of a large number of coefficients. In this paper, the homotopy algorithm is applied to the parameter identification of Magic Formula tyre model. A morphing parameter is introduced to correct the optimization process; as a result, the solution is directed converging to the global optimal solution, avoiding the local convergence. The method uses different continuation methods to globally optimize the parameters, which ensures that the prediction of the Magic Formula model can be very close to the test data at all stages of the optimization process.

Active steering systems can help the driver to master critical driving situations. This paper presents a fuzzy logic control strategy on active steering vehicle based on a multi-body vehicle dynamic model. The multi-body vehicle dynamic model using ADAMS can accurately predict the dynamic performance of the vehicle. A new hybrid steering scheme including both active front steering (applying an additional front steering angle besides the driver input) and rear steering is presented to control both yaw velocity and sideslip angle. A set of fuzzy logic rules is designed for the active steering controller, and the fuzzy controller can adjust both sideslip angle and yaw velocity through the co-simulation between ADAMS and the Matlab fuzzy control unit with the optimized membership function. To ensure the design of high-quality fuzzy control rules, a rule optimization strategy is introduced.

To design and optimize the vehicle driveline is necessary to decrease the fuel consumption and improve dynamic performance. This paper describes a methodology to optimize the driveline design including the axle ratio, transmission shift points and transmission shift ratios considering uncertainty. A new and flexible tool for modeling multi-domain systems, Modelica, is used to carry out the modeling and analysis of a vehicle, and the multi-domain model is developed to determine the optimum design in terms of fuel economy, with determinability. Secondly, a robust optimization is carried out to find the optimum design considering uncertainty. The results indicate that the fuel economy and dynamic performance are improved greatly.

Connected and automated vehicles (CAVs) can improve traffic efficiency and reduce fuel consumption. This paper proposes a cooperative game approach to merging sequence and optimal trajectory planning of CAVs at unsignalized intersections. The trajectory of the vehicles in the control zone is optimized by the Pontryagin minimum principle. The vehicle's travel time, fuel consumption, and passenger comfort are considered to construct the joint cost function, completing the optimal trajectory planning to minimize the joint cost function. Analyzing the different states between neighboring CAVs at the intersection to calculate the minimum safety interval. The cooperative game approach to merging sequence aims to minimize the global cost and the merging sequence of CAVs is dynamically adjusted according to the gaming result. The multi-player games are decomposed into two-player games, to realize the goal of the minimal global cost and improve the calculation efficiency.

This paper deals with the robust design of the Load Sensing Proportional Valve (LSPV). To find out the parameters which have main effect on the performance of the LSPV, the DOE based on orthogonal experiment is carried out utilizing the LSPV model built in AMESim environment. In order to save computation expense, the RSM technique is used to approximate the optimal objectives and constraints. Then a robust design methodology using multi-objective evolutionary algorithm (MOEA) is performed and a set of non-dominated solutions are therefore obtained. With specified assessments, feasible solutions can therefore be selected from the entire field of the Pareto optimal solutions. The validation is made by Monte Carlo Simulation Technique in terms of the robustness of the feasible solutions.

As is known to all, there are some contradictions between the handling and ride performance during the design process of vehicles. Sometimes owing to serious collisions of each criterion in the high-dimensional solution space, the common method to deal with the contradiction is to transform into a single target according to weights of each objective, which may not obtain a desired result. A multi-criteria approach is therefore adopted to optimize both properties and the result of a multi-criteria design is not a unique one but a series of balanced solutions. This paper is focused on the robust design of a simplified vehicle model in terms of not only ride comfort but also handling and stability using a multi-objective evolutionary algorithm (MOEA) method. Using the proposed method, the conflicting performance requirements can be better traded off. One of the most important indexes to characterize the vertical ride comfort is the acceleration of the sprung mass.

In autonomous driving, variations in tire vertical load, tire slip angle, road conditions, tire pressure and tire friction all contribute to uncertainty in tire cornering stiffness. Even the same tire may vary slightly during the manufacturing process. Therefore, the uncertainty of tire cornering stiffness has an important influence for autonomous driving path planning and control strategies. In this paper, the Chebyshev interval method is used to represent the uncertainty of tire cornering stiffness and is combined with a model predictive control algorithm to obtain the trajectory interval bands under local path planning and tracking control. The accuracy of the tire cornering stiffness model and the path tracking efficiency are verified by comparing with the path planning and control results without considering the corner stiffness uncertainties.

The vehicle ride comfort behavior is closely associated with the vibration isolation system such as the primary suspension system, the engine mounting system, the cab suspension system and the seat suspension system. Air spring is widely used in the cab suspension system for its low vibration transmissibility, variable spring rate and inexpensive automatic leveling. The mathematical model of the air spring is presented. The amplitude and frequency dependency of the air spring's stiffness characteristic is highlighted. The air spring dynamic model is validated by comparing the results of the experiment and the simulation. The co-simulation method of ADAMS and AMESim is applied to integrate the air spring mathematical model into the cab multi-body dynamic model. The simulation and ride comfort test results under random excitation are compared.

For vehicles equipped with dry dual clutch transmission, due to the diversity of starting conditions, it is a nontrivial task for control strategy to meet the requirements of all kinds of complex starting conditions, which is easy to cause large starting shock and serious clutch wear. Therefore, it is proposed in this paper an adaptive control strategy for complex starting conditions by adjusting two clutches to participate in the starting process at the same time. On the basis of establishing the transmission system model and clutch model, the starting conditions are identified in terms of starting speed, road adhesion and driver's intention, in which the driver's intention is identified by fuzzy reasoning model. Based on the identification of starting conditions and considering the safety principle, it is selected the appropriate starting gear and clutch combination mode, and adjusted the combination speed of the two clutches to carry out an adaptive control strategy.

Vehicle Thermal Management System (VTMS) is a crosscutting technology affecting the fuel consumption, engine performance and emissions. With the new approved fuel economy targets and the enhanced vehicle performance requirements, the ability to predict the impact on the fuel consumption of different VTMS modifications is becoming an important issue in the pre-prototype phase of vehicle development. This paper presents a methodology using different simulation tools to model the entire VTMS in order to understand and quantify its behavior. The detailed model contains: engine cooling system, lubrication system, powertrain system, HVAC system and intake and exhaust system. A detail model of the power absorbed by the accessory components operating in VTMS such as pumps and condenser is presented. The power of the accessory components is not constant but changing with respect to engine operation. This absorbed power is taken into account within the power produced by the engine shaft.

In order to reasonably match the variable stiffness and location of the Powertrain Mounting System (PMS) and optimize the ride comfort of commercial vehicle, a thirteen degrees of freedom (DOF) model of a commercial vehicle was established in Adams/view. Specially, the support rod installed on the upside of the transmission case was modeled as a flexible body. The vibration isolation provided by the PMS was evaluated in three aspects: the energy decoupling of the powertrain, the response force of the mount and the displacement of the powertrain. The energy decoupling ratio, the force RMS of the mount when force excitation was applied on the powertrain and the displacement of the powertrain Center of Gravity (C.G) when displacement excitation was applied on the vehicle chassis were selected as the optimal target. Adams and MATLAB were integrated into the optimization software iSIGHT to optimize the PMS. NSGA-II is used to obtain some Pareto-optimal solutions of PMS.

The powertrain mounting system (PMS) plays an important role in improving the NVH (Noise, Vibration, Harshness) quality of the vehicle. In all running conditions of a vehicle, the displacements of the powertrain C.G. should be controlled in a prescribed range to avoid interference with other components in the vehicle. The conventional model of PMS is based on vibration theory, considering the rotation angles are small, ignoring the sequence of the rotations. However, the motion of PMS is in 3D space with 3 translational degrees of freedom and 3 rotational degrees of freedom, when the rotation angles are not small, the conventional model of PMS will cause errors. The errors are likely to make powertrain interfering with other components. This paper proposes a rigid body mechanics model of the powertrain mounting system. When the powertrain undergoes a large rotational motion, the rigid body mechanics model can provide more accurate calculation results.

Interval inverse problems can be defined as problems to estimate input through given output, where the input and output are interval numbers. Many problems in engineering can be formulated as inverse problems like vehicle suspension design. Interval metrics, instead of deterministic metrics, are used for the suspension design of a vehicle vibration model with five degrees of freedom. The vibration properties of a vehicle vibration model are described by reasonable intervals and the suspension interval parameters are to be solved. A new interval inverse analysis method, which is a combination of Chebyshev inclusion function and optimization algorithm such as multi-island genetic algorithm, is presented and used for the suspension design of a vehicle vibration model with six conflicting objective functions. The interval design of suspension using such an interval inverse analysis method is shown and validated, and some useful conclusions are reached.