Commercial Vehicle Model Research Articles

Virtual battery electric vehicle development via 1D tools

Actual testing and prototyping costs make up a significant portion of engineering budgets. Virtual demonstration mainly relies on fast and accurate models with robust performance prediction capability as a cost-effective solution. In this manuscript, GT-Suite, a one-dimensional simulation tool is preferred for developing an isothermal battery model. The developed battery model is implemented to a Light Commercial Vehicle model to run Worldwide Harmonized Light Vehicles Test Cycle. The critical outputs such as state of charge, energy depletion, heat rejection, and generated power are reported. Histograms such as pack current, charge, and discharge current with respect to its nominal capacity (C-rate) are also created to examine the operation capability of battery. In the results, it is seen that the state of charge diminishes from 90% to 82%, as an expected behavior. It is also found that the Parallel Sparse Direct and Multi-Recursive Iterative Linear Solvers methodology reduces the simulation duration by approximately 100 times, in comparison with Singular Value Decomposition Electrical Inversion Scheme. The runtime of the battery pack modeled with the cellular approach combined with the SVD method is more than 90 h. However, the runtime drops to 0.75 h when the PARDISO technique is applied. The method developed within this study can be used for rapid and accurate development of batteries. The verification can be completed in virtual environment and a vital reduction in engineering/prototype/test costs can be guaranteed. The innovation the developed methodology propose is ensuring a fast and reliable performance assessment via taking the holistic effect of integrated models into consideration. Hence it is possible for original equipment manufacturer to completely or gradually eliminate the actual tests and hence prototype costs, test system, and engineer allocations.

Establishment of a two-axis commercial vehicle 6DOF prediction model for nonlinear MPC controller

Most of the commercial vehicle dynamics models used by nonlinear MPC controllers are 3-DOF models, which do not reflect the motion constraints of sprung and unsprung masses, the coupling relationship between translational and rotational motion, and the coupling characteristics of lateral and longitudinal tire forces, so it is difficult to meet the model prediction requirements under extreme working conditions. Therefore, according to the dynamics theory, this paper firstly establishes a 14DOF model which can reflect the movement characteristics of the sprung mass in the lateral, longitudinal, and vertical space, the suspension characteristics and the movement characteristics of the wheels on both sides. Then, in order to reduce the computational burden of the model prediction and make it applicable to the nonlinear MPC controller, the 14DOF model is simplified to the 6DOF model. Finally, the established 6DOF model and the classical 3DOF commercial vehicle model were compared and evaluated based on the error in prediction horizon and performance in trajectory tracking. The results show that the model that, in extreme working conditions, the new 6DOF model has obvious accuracy advantages compared with the classical 3DOF model in the prediction horizon, and can achieve convergence to the reference states faster, so as to obtain a solution efficiency similar to or even higher than 3DOF.

Experiment and simulation study of waste heat recovery of REEV based on different structures and control strategies

In order to reduce the engine fuel consumption and power battery energy consumption of REEV(Range Extend Electric Vehicle)under low temperature driving, this work changes the battery cooling preheat circuit from air-cooling to water circulation on a commercial vehicle model. The waste heat from the motor is also utilized in the cabin through a heat exchanger to assist the PTC heat generation. Under the same conditions, simulations and experiments showed a 0.54 % increase in fuel consumption and a 0.55 % reduction in battery energy consumption. In order to further reduce the energy consumption of REEV under low temperature driving, this paper uses PID, MCCS and BPNN-MCCS to control the low temperature PTC heating power and cabin inlet airflow. The comparison with the ON-OFF control shows that the energy consumption is reduced by 1.56 %, 2.2 %, and 2 % respectively compared to the original.

A lateral trajectory tracking control method for intelligent commercial vehicles considering active anti‐roll decision based on Stackelberg equilibrium

Existing research on path following strategies generally does not consider the interference effect of active anti-roll (AAR) action. This seriously affects the driving safety under extreme obstacle avoidance and other conditions. Therefore, based on the non-cooperative Stackelberg equilibrium theory, this research proposes a lateral trajectory tracking strategy that considers AAR decision. First, a yaw-roll coupled dynamic model of commercial vehicle with front wheel angle and AAR moment as input is established to describe the coupling effect of vehicle lateral and roll motions. Then, based on the Stackelberg equilibrium theory, active front steering (AFS) system and AAR bar system are modelled as the leader and follower in the leader–follower collaborative control strategy, respectively. Finally, simulation and experiments show that the leader–follower collaborative control strategy can effectively improve the control conflict between the two systems and improve the anti-roll performance during trajectory tracking.

Modeling the Impacts of Off-Peak Delivery in the Greater Toronto and Hamilton Area

Off-peak-hour delivery (OPHD) has the potential to reduce congestion in busy urban areas and at the same time improve the efficiency of logistics providers, shippers, and receivers. There has been growing interest in OPHD in the Greater Toronto and Hamilton Area (GTHA), an important freight hub in Canada. The Government of Ontario is considering permanently relaxing noise by-laws to promote OPHD throughout the province. The purpose of this study is to provide quantitative assessments of the impacts of region-wide adoption of OPHD for the GTHA. A recently developed commercial vehicle (CV) model for the GTHA is presented in the paper. Various OPHD scenarios have been tested with the CV model. The impacts of induced passenger demand have also been demonstrated. Modeling outcomes indicate that OPHD could result in 5,530 vehicle-hours saved in a day after induced demand is accounted for. Light truck carriers would benefit the most by shifting to off-peak hours and prioritizing Toronto and Peel Region customers would yield the highest travel time savings during the off-peak hours.

Study on FE-SEA Modeling and Acoustic Performance of Heavy Duty Commercial Vehicle Based on Experimental Statistical Energy Parameters

Due to the difficulty of obtaining statistical energy parameters of complex structures and the complexity of modeling connection and model verification, the hybrid FE-SEA model has many problems in modeling complex structures. Therefore, in order to solve the above problems, this paper provides a reference for the application of the hybrid FE-SEA model in complex structures. In this paper, the hybrid FE-SEA commercial vehicle model is established by an experimental statistical energy parameter modeling method and a modification method. The model division and subsystem connection modeling of a complex substructure of a heavy vehicle cab are studied. In the hybrid model, the hybrid line connection and the hybrid point connection are established. On this basis, the parameters of the cab model were studied, and the statistical energy parameters such as modal density, internal loss factor, and coupling loss factor were obtained by the experimental method. The statistical energy parameters of the cab acoustic model are modified. Finally, the accuracy of the model is verified by vehicle test. In addition, the acoustic performance of the cab was optimized, and airtightness and acoustic packaging were verified. The full parameter modeling and correction method is adopted in this paper, which is an effective supplement to the traditional statistical energy parameter modeling method.

Roll Angle Estimation of a Motorcycle through Inertial Measurements.

Currently, the interest in creating autonomous driving vehicles and progressively more sophisticated active safety systems is growing enormously, being a prevailing importance factor for the end user when choosing between either one or another commercial vehicle model. While four-wheelers are ahead in the adoption of these systems, the development for two-wheelers is beginning to gain importance within the sector. This makes sense, since the vulnerability for the driver is much higher in these vehicles compared to traditional four-wheelers. The particular dynamics and stability that govern the behavior of single-track vehicles (STVs) make the task of designing active control systems, such as Anti-lock Braking System (ABS) systems or active or semi-active suspension systems, particularly challenging. The roll angle can achieve high values, which greatly affects the general behavior of the vehicle. Therefore, it is a magnitude of the utmost importance; however, its accurate measurement or estimation is far from trivial. This work is based on a previous paper, in which a roll angle estimator based on the Kalman filter was presented and tested on an instrumented bicycle. In this work, a further refinement of the method is proposed, and it is tested in more challenging situations using the multibody model of a motorcycle. Moreover, an extension of the method is also presented to improve the way noise is modeled within this Kalman filter.

Control of Sunroof Buffeting Noise by Optimizing the Flow Field Characteristics of a Commercial Vehicle

When a commercial vehicle is driving with the sunroof open, it is easy for the problem of sunroof buffeting noise to occur. This paper establishes the basis for the design of a commercial vehicle model that solves the problem of sunroof buffeting noise, which is based on computational fluid dynamics (CFD) numerical simulation technology. The large eddy simulation (LES) method was used to analyze the characteristics of the buffeting noise with different speed conditions while the sunroof was open. The simulation results showed that the small vortex generated in the cab forehead merges into a large vortex during the backward movement, and the turbulent vortex causes a resonance response in the cab cavity as the turbulent vortex moves above the sunroof and falls into the cab. Improving the flow field characteristics above the cab can reduce the sunroof buffeting noise. Focusing on the buffeting noise of commercial vehicles, it is proposed that the existing accessories, including sun visors and roof domes, are optimized to deal with the problem of sunroof buffeting noise. The sound pressure level of the sunroof buffeting noise was reduced by 6.7 dB after optimization. At the same time, the local pressure drag of the commercial vehicle was reduced, and the wind resistance coefficient was reduced by 1.55% compared to the original commercial vehicle. These results can be considered as relevant, with high potential applicability, within this field of research.

Research on Path Tracking and Anti-roll Control of Commercial Vehicle Based on Takagi-Sugeno Fuzzy Model

Abstract With the increasing demand for intelligent commercial vehicles, the path tracking technology of commercial vehicle autonomous driving systems has become a research hotspot. However, commercial vehicles are prone to roll over when they are making an emergency obstacle avoidance or making a sharp turn on the road surface with high adhesion coefficient, resulting in serious traffic accidents. In this paper, a steering control method based on the T-S fuzzy model for automatic driving of commercial vehicles is proposed, which takes path tracking and anti-roll as control objectives. Firstly, the three-degree-of-freedom model of commercial vehicle and the vehicle-road dynamic model was established to obtain the vehicle-road general model. Then, considering the influence of the nonlinear change of vehicle speed on the system performance, the speed is taken as the variable parameter of the system. Taking the speed as the prerequisite variable, the fuzzy rule is designed, and the vehicle-road model is transformed into a T-S fuzzy model. Then, the fuzzy controller is designed according to the Lyapunov method and the parallel distributed compensation (PDC) algorithm. Finally, sufficient conditions for the system to satisfy the H∞ performance index under the action of the fuzzy controller are given in the form of linear matrix inequality (LMI). LMI toolbox is used to solve the problem, and the robustness of the system is guaranteed. Simulation results show that the system can ensure the accuracy of path tracking and greatly reduce the risk of vehicle rollover.

Comparison of two Multiphase Procedures on a Commercial Vehicle in Rain Conditions

In automotive design, the study of the water thin layer over a car due to rain is becoming increasingly important: the challenge is to obtain a way to describe the behavior of the water over a vehicle in rainy conditions and its interactions with wipers and drainage systems, to determine potential failures of the vehicle design. In this paper two similar numeric procedures have been realized with the software STAR CCM+® to analyze the dynamic of water thin layer starting from the impingement of the rain on the car surface and taking into account even the motion of the wipers over the windshield. Moreover, the water that flows through the drainage systems is monitored to figure out if the water could produce a malfunction of components near them. In order to describe each status of the water, many multiphase models are used. These methodologies have been applied on a commercial vehicle model and the results have been examined and compared to each other. The analysis shows a better description of the reality for one of them, leading to the possibility of using it as a design tool in the automotive industry.

Development of a Heavy Duty Commercial Vehicle Dynamic Model with a Hydraulic-Mechanical Transmission Model Based on Field Test Results of a Vehicle with Automatic Transmission

The modeling of dynamic systems is advantageous for saving time and effort when developing new systems. In the automobile industry, making a model is beneficial for predicting the feasibility and performance of a conceptual design. Hence, in this study, a heavy duty commercial vehicle with an Automatic Transmission (AT) was tested, and the model was developed and verified. A conceptual design model of Hydraulic-Mechanical Transmission (HMT) was then developed. The commercial vehicle model and the HMT model were integrated and compared to evaluate the feasibility and the difference in performance.

MATHEMATICAL AND COMPUTER SIMULATION OF THE COMMERTIAL VEHICLE’S HYDRAULIC RETARDER

Introduction.The article represents the mathematical model of commercial vehicle’s hydraulic retarder. The model is based on the mathematical model of the variable filling hydraulic dynamometer.Materials and methods.The retarder model was designed with the possibility of its integration with the mathematical model of the engine cooling system. For this purpose, the state function of fluid temperature in a working chamber of the retarder was added to the retarder model. Consequently, fluid compression in the working chamber was included into the model to avoid unlimited filling because of possible high pressure at the retarder inlet.Results.The simulation model of the retarder was established as LMS Amesim submodel using C-programming language. For testing, the retarder simulation model was integrated with the Amesim models of the engine cooling system and with the powertrain and vehicle movement dynamics. In addition, brake torque regulation wassynthesized on PI controllers.Discussion and conclusions. During simulation of the vehicle movement on the mountain route expectable results were obtain, such as continuous braking via the retarder, which led to increasing of the cooling system’s fluid temperature. Therefore, overfilling of the retarder working chamber didn’t occur through the fluid compression. The retarder model could be applied to determine retarder design influence at vehicle functioning. For instance, it could be used for development of the algorithms’ control.

Fault Detection for Automotive Shock Absorber

Fault detection for automotive semi-active shock absorbers is a challenge due to the non-linear dynamics and the strong influence of the disturbances such as the road profile. First obstacle for this task, is the modeling of the fault, which has been shown to be of multiplicative nature. Many of the most widespread fault detection schemes consider additive faults. Two model-based fault algorithms for semiactive shock absorber are compared: an observer-based approach and a parameter identification approach. The performance of these schemes is validated and compared using a commercial vehicle model that was experimentally validated. Early results shows that a parameter identification approach is more accurate, whereas an observer-based approach is less sensible to parametric uncertainty.

Dynamic Choice Model of Urban Commercial Activity Patterns of Vehicles and People

Intraurban commercial vehicle travel is a relatively underdeveloped aspect of urban travel demand modeling despite the large share of the weekday traffic stream represented by commercial movements. One problem is the proprietary nature of these data and the corresponding lack of behavioral understanding of how establishments schedule their trips. Even when such data have been made available, such as through establishment travel surveys, the large variation in firm size, commodities and services, and logistics practices makes it difficult to create a generalized decision framework. This work uses establishment survey data collected by the Ohio Department of Transportation to create an intraurban commercial vehicle model to be run in a disaggregate microsimulation environment and focuses on commercial movement patterns. The model generates entire daily patterns for workers who regularly travel as part of their jobs and creates tours through a dynamic choice process that incrementally builds tours, taking into consideration elapsed time and time of day in next-stop purpose and location choices. Activity durations are embedded in the utility equations of “stay” alternatives and provide internal consistency between the dimensions of activity purpose, duration, time of day, and location. Model formulation and estimation results are presented for the dynamic activity choice model component. The model system can reproduce observed commercial travel patterns found in the survey data and provide intuitively plausible interpretations for commercial travel behavior in the absence of more detailed knowledge of individual and firm operations.

Development of a Fleet Allocator Model for Calgary, Canada

The Calgary commercial vehicle model is an attempt to model all commercial vehicle movements in Calgary, Alberta, Canada, as part of a larger model system that includes a personal travel model. One type of commercial vehicle initially modeled in a simple, gravity-based fashion because of limited data is the fleet allocator. Fleet allocators are commercial vehicles that make many stops in a coordinated pattern. These include services such as garbage pickup, newspaper and mail delivery, and couriers. From an existing linear regression trip generation model and a gravity-based distribution model, a more complex tour-based model system consistent with the approach for the remainder of the commercial vehicles was adopted. With available aggregate fleet allocator information provided with the cooperation of the City of Edmonton, Canada, along with the parameters estimated for other types of commercial vehicles in the existing tour-based Calgary commercial vehicle model, a full tour-based fleet allocator model was developed and calibrated to match the available observed data. The process used was a successful demonstration of using an existing model to cover a different set of movements by calibrating the model parameters using the additional available data.