Complete Vehicle Model Research Articles

A comprehensive estimation method for vehicle motion states based on model constraints

The motion state estimation is indispensable for unmanned ground vehicles. Most traditional methods estimate individual states and utilize high-dimensional dynamics models that necessitate extensive prior information to improve accuracy. However, these approaches are beset with numerous challenges in the accuracy, complexity, and computational burden. In this paper, a novel method is proposed to address these problems with two novelties. Firstly, it possesses the capability to simultaneously estimate 10 fundamental states, including vehicle velocities, wheel slip ratios, and wheel sideslip velocities. The estimation accuracy is augmented since the coupling relationships among states are considered. Secondly, the method avoids the utilization of the complete vehicle model, instead employing the constraints derived from the models, thereby the requisite prior information and computational burden can be reduced. The accuracy of the proposed method was demonstrated through simulation experiments and field tests, as well as its robustness in challenging situations, such as the wheel slip.

Unique Approach of Modern Automotive Exhaust System Mountings Design for NVH Improvement

<div>Minimizing vibration transmitted from the exhaust system to the vehicle’s passenger compartment is the primary goal of this article. With the introduction of regulatory norms on NVH behavior and emissions targets, it has become necessary to address these issues scientifically. Stringent emissions regulations increased the complexity of the exhaust system resulting in increased size and weight. Exhaust system vibration attenuation is essential not only from the vehicle NVH aspects but also for the optimized functionality of the subsystems installed on it. Based on earlier studies, this work adopts a more thorough strategy to reduce vehicle vibration caused by the exhaust system by adjusting it to actual operating conditions.</div> <div>To achieve this, a complete vehicle model of 22 DOF is considered, which consists of a powertrain, exhaust system, chassis frame, and suspension system. A method for evaluating static and dynamic vibration response is proposed. Through the use of the vehicle’s rigid body modes and actual field events, design indicators are carefully analyzed and validated. Based on actual operating conditions, the two main load cases that are taken into consideration are idling and the sweet spot operating zone. To define the sweet spot zone of the dominant vehicle/engine-operating scenario, the vehicle duty cycle is monitored experimentally.</div> <div>The baseline 22 DOF model results show a degradation in exhaust vibration performance in both load cases as its yaw and bounce modes are falling into the resonance region of the idle and sweet spot operating zone load cases, respectively. The acceleration reduction of nearly 10–20 dB in static events, and nearly 10 dB in dynamic events can be evident in the proposed model. The proposed system’s outcomes demonstrate an improvement in the eigenvalues of the yaw and bounce modes, which in turn enhances the vehicle’s overall NVH performance in both static and dynamic load cases. Thus, the study suggests that designers should consider the real field events’ load cases for modern exhaust system-mounting optimization to achieve improvement in NVH behavior, fuel efficiency, emissions performance, and durability aspects of the vehicle.</div>

Research on driving condition recognition in hybrid electric vehicle energy management strategy

Abstract The driving conditions encountered by vehicles during operation are complex and varied, and the ECMS (Equivalent fuel Consumption Minimization Strategy) based on minimum equivalent fuel consumption has poor adaptability to different driving conditions. To optimize the adaptability of the ECMS and improve the overall vehicle economy, this paper proposes an operating condition recognition model based on the Back Propagation neural network algorithm to optimize the ECMS energy management control strategy. Firstly, three types of driving conditions were identified: urban, suburban, and high-speed conditions. A complete vehicle model was constructed on the Matlab/Simulink platform. The efficacy of the strategy, before and after optimization, is verified under the WLTP (Worldwide Harmonized Light Vehicles Test Procedure) driving cycle. Simulation results show that the optimized ECMS can better adjust the power apportionment among the engine and motor, reducing the fuel consumption per hundred kilometers by 4.01% and thereby enhancing the overall vehicle economy.

Suspension and tyre loads estimation of an FSAE car: model development and on-track validation

In this paper a relatively simple model is presented, able to compute the loads on the suspension arms and at the tyres' contact patches of a Formula SAE car starting from telemetry data. The model is based on standard dynamic equilibrium equations, a simplified assumption for the limited-slip differential and a given front-to-rear brake distribution. The model inputs are the signals acquired with common telemetry sensors, which usually equip a Formula SAE vehicle (Inertia Measurement Unit, GPS, potentiometers, Hall sensors). In order to validate the model, some arms of the suspensions were instrumented with strain gauges, and a kinematic model of the suspension, together with its static equilibrium equation set, was set up to relate the arm loads to the forces acting at the tyre-road contact patch. The suspension kinematic and equilibrium models were first validated through static tests, with known forces applied at the wheel hub. Then, the complete vehicle model was validated by comparing the same quantities, relative to some real driving tests on a kart circuit, showing a fairly good agreement between the predicted and the measured loads. The model represents a valuable tool for vehicle design and development for the Formula SAE team.

Adaptive ECMS based on speed forecasting for the control of a heavy-duty fuel cell vehicle for real-world driving

Aiming at reducing pollutant emissions, hydrogen and fuel cell hybrid electric vehicles (FCVs) represent a promising technological solution. In this scenario, this paper proposes an adaptive energy management strategy (A-EMS) based on speed forecasting for a heavy-duty FCV, in order to achieve stable battery charge sustenance in realistic driving conditions. A validated and optimized fuel cell system model has been integrated into a complete vehicle model developed in the GT-Suite environment. A short-term velocity prediction layer based on a long short term memory (LSTM) neural network has been built in the A-EMS framework. The network has been trained and tested with realistic driving data simulated by GT-Real Drive for routes of the Trans-European Transport Network. The vehicle speed prevision has been realized over different forecasting horizons (5, 10, and 20 s). The adaptive equivalent consumption minimization strategy (A-ECMS) combined with short-term vehicle speed prediction is the A-EMS core algorithm of the presented work. Its results are here compared with the standard ECMS (S-ECMS) for four different driving cycles, including both standardized (HDDT) and realistic driving profiles. Three different European routes, with varying characteristics and from different countries, have been selected to test the proposed strategy in various conditions. The short-term prediction layer achieves satisfactory forecasting accuracy, with a RMSE ranging from 1.76 km/h to 13.37 km/h. The A-ECMS provides an improved by an order of magnitude battery charge sustenance, evaluated in terms of maximum battery state of charge (SoC) variation and fluctuation degree, with a hydrogen consumption increase ranging from 3.76% to 11.40% compared to the S-ECMS, for which the driving cycle is supposed to be known beforehand. As an example, in the HDDT cycle, the absolute maximum SoC variation and its fluctuation degree are lowered by about 76% and 79%, respectively. In conclusion, the proposed A-ECMS demonstrated that it is applicable for real driving conditions without prior knowledge of the driving cycle while improving battery charge sustaining for a FCV.

Effect of levitation gap feedback time delay on the EMS maglev vehicle system dynamic response

EMS maglev train uses the active control system to maintain the levitation stability, time delay is widespread in control system. However, the existing maglev dynamics studies rarely consider the effect of time delay, so these analysis results cannot directly guide the engineering design. This paper starts from a theoretical analysis of the levitation stability of a single electromagnet levitation system to obtain the theoretical critical value for the time delay. Then the model is gradually extended to a complete vehicle model and a vehicle-girder coupling dynamics model to find the time delay engineering critical values for the complex coupling system. In order to seek ways to reduce the influence of time delay on the dynamic responses, this paper analyzes the influence regularities of the running speed and control parameters on the dynamic response under the effect of time delay. The result shows that the theoretical critical value of the time delay is equal to the ratio of the differential coefficient and proportional coefficient of the PID controller. For a complex maglev system, the engineering critical value is less than the theoretical critical value. Higher running speeds lead to time delay having a more obvious effect on the maglev system’s dynamic responses. Selecting the smaller proportional coefficient and appropriate differential coefficient for the levitation control system can expand the stability region and reduce the influence of time delay on the maglev system. This analysis is helpful and meaningful to the understanding of the EMS vehicle system stability, and helpful to explore the reason of violent coupled vibration in actual engineering.

Concept for Generating Energy Demand in Electric Vehicles with a Model Based Approach

Hybrid energy storage systems (HESS) for electric vehicles, which consist of lithium-ion batteries and supercapacitors, have become an increasing focus of research and development in recent years. The combination of the two combines the advantages of each storage technology (high energy density in batteries and high power density in supercapacitors) in one system. To effectively manage the energy flow between these two different storage technologies, an intelligent energy management system (EMS) is required. In the development of the EMS, it is usual to run preliminary checks in a simulation environment that is as close to reality as feasible already during the development process. For this purpose, this paper presents a concept for the creation of a simulation environment consisting of realistic routes and a holistic vehicle model. The realistic route data are generated by a route-generating algorithm, which accesses different map services via application programming interfaces (API) and retrieves real route data to generate a simulated route. By integrating further online services (e.g., OpenWeather API), the routes are further specified with, for example, real weather data, traffic data, speed limits and altitude data. For the complete vehicle model, components including the suspension, chassis and auxiliary consumers are simulated as blackbox models. The components that can be accessed during the simulation are simulated as white box models. These are the battery, the supercapacitor, the DC/DC converter and the electric motor. This allows the EMS to control and regulate the HESS in real time during the simulation. To validate the simulation environment presented here, a real BMW i3 was driven on a real route, and its energy demand was measured. The same route was simulated in the simulation environment with environmental conditions that were as realistic as feasible (traffic volume, traffic facilities, weather) and the vehicle model of the BMW i3. The resulting energy demand from the simulation was recorded. The results show that the simulated energy consumption value differs by only 1.92% from the real measured value. This demonstrates the accuracy of the simulation environment presented here.

Evaluation Methodology for Physical Radar Perception Sensor Models Based on On-Road Measurements for the Testing and Validation of Automated Driving

In recent years, verification and validation processes of automated driving systems have been increasingly moved to virtual simulation, as this allows for rapid prototyping and the use of a multitude of testing scenarios compared to on-road testing. However, in order to support future approval procedures for automated driving functions with virtual simulations, the models used for this purpose must be sufficiently accurate to be able to test the driving functions implemented in the complete vehicle model. In recent years, the modelling of environment sensor technology has gained particular interest, since it can be used to validate the object detection and fusion algorithms in Model-in-the-Loop testing. In this paper, a practical process is developed to enable a systematic evaluation for perception–sensor models on a low-level data basis. The validation framework includes, first, the execution of test drive runs on a closed highway; secondly, the re-simulation of these test drives in a precise digital twin; and thirdly, the comparison of measured and simulated perception sensor output with statistical metrics. To demonstrate the practical feasibility, a commercial radar-sensor model (the ray-tracing based RSI radar model from IPG) was validated using a real radar sensor (ARS-308 radar sensor from Continental). The simulation was set up in the simulation environment IPG CarMaker® 8.1.1, and the evaluation was then performed using the software package Mathworks MATLAB®. Real and virtual sensor output data on a low-level data basis were used, which thus enables the benchmark. We developed metrics for the evaluation, and these were quantified using statistical analysis.

Study on ride comfort in post-braking phase based on brake-by-wire system

This paper focuses on both brake safety and ride comfort improvement in the postbraking phase. First, a complete vehicle model is established together with the design of a safety control strategy for the longitudinal deceleration control method. Information on driver behavior and vehicle signals is collected to ensure braking safety, including vehicle speed, vehicle deceleration, steering wheel angle, accelerator opening degree, and ABS status. Second, a methodology for longitudinal deceleration control is proposed using a sliding mode control algorithm, aiming to improve ride comfort in the postbraking phase under the prerequisite of a reduced braking distance. Finally, co-simulation, based on Simulink and CarSim, and vehicle tests are carried out. The results show that when the braking distance is constant, the longitudinal deceleration vibration and vertical pitch vibration in the postbraking phase are well suppressed. The peak overshot of longitudinal deceleration and the amplitude of vertical vibration in the postbraking phase decrease. The vibration period of the vehicle is shortened. The braking process of the vehicle is smoother. Thus, the ride comfort is improved in the postbraking phase while maintaining braking safety.

Determination of the optimal battery capacity of a PEM fuel cell vehicle taking into account recuperation and supercapacitors

Proton exchange membrane (PEM) fuel cell vehicles require an electrical intermediate storage system to compensate for dynamic load requirements. That storage system uses a battery and has the task to increase tolerance to dynamic operation. In addition, energy can be recuperated and stored in supercapacitors to increase the fuel cell vehicle’s efficiency. To determine the optimal battery capacity according to the recuperation potential and possible use of a supercapacitor, a reference vehicle with PEM fuel cell was transferred to the simulation environment Matlab/Simulink. The model is based on a cell model describing the electrochemical and physical interactions within the cell. It has been implemented in a complete vehicle model for the representation of a fuel cell vehicle. Various legal driving cycles, such as the WLTP (“Worldwide harmonized Light Vehicles Test Procedure”), were used for the calculations. A further step sets the optimal battery capacity depending on the dynamic of the fuel cell system. With this simulation model, dynamic requirements—for the fuel cell and the associated system components—can be determined in the future, scalable for each vehicle depending on the battery capacity and recuperation potential.

Optimization of the powertrain of electric vehicles for a given route

The global challenge of reducing pollutant and greenhouse gas emissions has forced the development of alternatives to traditional internal combustion engine vehicles, such as electric or hybrid vehicles. Electric engines are the most efficient for delivery trucks or city buses. Their acceleration and deceleration patterns make them inefficient for the use of internal combustion engines. However, their range and purchase cost are the main factors limiting their use in these applications. The range and acquisition cost of an electric vehicle are mainly related to the energy storage system. Therefore, the optimal size of the battery pack should be considered as a design objective when its application is known. This paper presents a methodology to optimize the battery pack of an electric vehicle based on a given travel distance in a target time. Therefore, it would be applicable to delivery vehicles, buses and any vehicle whose route and travel time are known in advance. The proposed methodology allows minimizing energy consumption by determining the optimal gear ratio for a given route, setting the travel time as a target. A complete vehicle model and a multi-objective genetic algorithm are used for this purpose.

Parameter Optimization of Pure Electric Vehicle Power System Based on Genetic Algorithm

In this paper, the ADVISOR software was used to establish a complete vehicle model of an electric vehicle, and the model was verified by CYC_NEDC under European urban conditions to meet the requirements. The maximum power of the driving motor, the speed ratio of the transmission system and the capacity of the storage battery are taken as the optimization objectives to carry out multi-objective optimization. Connect the model built by genetic algorithm and ADVISOR, run the program to simulate the two together, and get the result of parameter optimization of dynamic system. Through the simulation analysis and comparison under CYC_NEDC cycle conditions, the maximum speed, maximum climb slope, acceleration time and other dynamic performance parameters of this electric vehicle are effectively improved after optimization.

DESIGN, SIMULATION AND MATHEMATICAL MODELLING OF THE DYNAMIC BEHAVIOR OF A VEHICLE TIRE AND CHASSIS SYSTEM AT A TURN.

Road security has become with time a topic of concern in our society as per the increasing number of accidents and deaths occurring on the highways. Regulatory experts on road users have constantly been working for ways to solve this problem and thence better the lives of the citizens. This paper is aimed at proposing a mathematical model integrating specific parameters, describing the dynamic lateral behavior of a vehicle’s tire and chassis systems and enabling to state a relationship between road characteristics and vehicle dynamics. To achieve this, we made used of the fundamental theorems of dynamics for the modeling of the vehicle’s suspended and non-suspended masses and load transfers, then we associated this with the Pacejka Tire model to obtain a complete vehicle model. After the particularization of a global model, a simulator was realized named “DYNAUTO SIMULATOR” which iterates the given variables to produce a consistent result. After an experimental research made on the Ndokoti – PK 24 road section we could, thanks to our simulator determine the maximum speed to have at every turn of this road section and also understand the effect of the modification of a vehicle’s center of gravity on its stability. This work will be an important tool which can be recommended to the regulatory board as a major asset in the road construction policy and also in the improvement of road safety measures.

Motor Vector Control Based on Speed-Torque-Current Map

In order to effectively extend the mileage of pure electric vehicles, the influence of the electromechanical energy conversion principle and the dynamic control of a permanent magnet synchronous motor (PMSM) on the performance of pure electric vehicles are studied with a dual-motor drive system as a carrier in this paper. A vector control strategy based on the speed-torque-current map of a motor is proposed, considering the bus voltage fluctuation influenced by battery charge and discharge. By constructing a complete vehicle model including the dynamic control model of the motor, the power distribution control strategy of a dual-motor coupling mode considering the dynamic characteristics of the motor is developed and simulated on the MATLAB platform. The results show that the dynamic model of the motor is closer to the actual running conditions. The proposed control strategy effectively reduces the demand power, decreases the energy consumption of the electric drive system, and extends the mileage of the vehicle.

Open-Source Dynamic Matlab/Simulink 1D Proton Exchange Membrane Fuel Cell Model

This work presents an open-source, dynamic, 1D, proton exchange membrane fuel cell model suitable for real-time applications. It estimates the cell voltage based on activation, ohmic and concentration overpotentials and considers water transport through the membrane by means of osmosis, diffusion and hydraulic permeation. Simplified equations reduce the computational load to make it viable for real-time analysis, quick parameter studies and usage in complex systems like complete vehicle models. Two modes of operation for use with or without reference polarization curves allow for a flexible application even without information about cell parameters. The program code is written in MATLAB and provided under the terms and conditions of the Creative Commons Attribution License (CC BY). It is designed to be used inside of a Simulink model, which allows this fuel cell model to be used in a wide variety of 1D simulation platforms by exporting the code as C/C++.

Feasibility Study of an Innovative Urban Electric-Hybrid Microcar

This paper presents the feasibility study of a new platform for electric-hybrid quadricycles, developed by addressing important concepts like passive safety and comfort, which often represent a shortcoming in this vehicle category. Starting from packaging of energy storage system and macroscopic subsystems as the main technological constraint, the study has been entirely developed in a virtual environment, with finite element verifications on preliminary models, and a subsequent cooperation phase between computer aided design and finite element analysis softwares, with a guideline for the main tests being that each could feasibly be carried out on a complete vehicle model in order to validate the original assumptions. The resulting design, with a body curb mass of less than 100 kg, was capable of integrating optimal static stiffness characteristics and crash performance, together with improved vehicle dynamics thanks to an innovative suspension archetype.

EV Traction Control Based on Nonlinear Observers Considering Longitudinal and Lateral Tire Forces

An observer-based traction control strategy for electric vehicles is proposed in this paper. The proposed strategy considers the combined effects of lateral and longitudinal traction forces, both for acceleration and regenerative braking, even in curved trajectories. Nonlinear reduced-order observers are designed for estimating tire-road friction condition on each traction wheel and vehicle lateral velocity from which side-slip angles are calculated. A detailed analysis of observers convergence is performed, and a method to know the quality of the estimated variables is also proposed. The proposed traction control strategy allows avoiding the traction wheels skidding during acceleration and braking both in straight trajectories and turning maneuvers. The performance of the proposal is verified through simulation on a complete vehicle model, under different situations and even considering a different vehicle tire model.

CFD investigation on wheel rotation modelling

It is well understood in the automotive community that wheels are a major contributor to the aerodynamic drag of passenger vehicles. The flow around rotating wheels is very complex due to the many separation regions created by very small tyre features and by the contact area of the tyre with the ground. Correct modelling of wheel rotation requires accuracy in the representation of the tyre geometry and proper boundary conditions to simulate the rotation. This paper proposes a hybrid approach for simulating tyre rotation which is simple to implement and does not suffer from the limitations of a sliding mesh approach, at the region where the tyre meets the ground. The method is first evaluated on a single wheel that is free standing and the results are compared to a full sliding mesh computation, which is considered to be the best possible numerical solution. The technique is then implemented on a complete vehicle model simulation and the results are compared against wind tunnel force measurements. The good agreement obtained in these test cases shows that the proposed approach is a promising solution to a more accurate numerical simulation of rotating wheels.

Lightweighting in light commercial vehicles: cradle-to-grave life cycle assessment of a safety-relevant component

Currently, the reduction of weight in automotive is a very important topic in order to lower the air pollution. In this context, the purpose of the present paper was to analyze a real case study through a comparison of the environmental sustainability between a conventional steel crossbeam for light commercial vehicles and an innovative lightweight aluminum one. For both scenarios, a cradle-to-grave life cycle assessment methodology and a sensitivity analysis has been used through the study of the following phases: mineral extraction, component manufacturing, use on vehicle, and end of life. In particular, many primary data and a complete vehicle model simulation with three different European driving cycles have been used in order to reach the highest possible level of accuracy during the analysis. Regarding the manufacturing phase, the aluminum component’s production gave the highest impact because of the high energy required in the mineral reduction. Anyway, this stage of the analysis had a low effect on the entire LCA, because the benefit of weight reduction during vehicle use showed a strongly higher contribution. The urban driving cycle had the most relevant impact, as a consequence of the frequent start and stop operations and the longest time with engine at idle speed, while the extra-urban cycle is the less demanding due to its higher average speed and no start and stop. In conclusion, the present research demonstrated the environmental importance of the lightweight for an actual case study in the commercial vehicles field.

Control de Tracción para un Vehículo Eléctrico basado en Observadores no Lineales

<p>En este trabajo se propone una estrategia de control de tracción para un vehículo eléctrico de cuatro ruedas, basada en observadores no lineales que permiten estimar la fuerza máxima que se puede transferir al suelo. El conocimiento de la fuerza máxima permite realizar un control del deslizamiento de los neumáticos de tracción, evitando que las ruedas patinen aún en superficies de baja adherencia. La estrategia propuesta permite además evitar que se produzca un momento de guiño no deseado en el vehículo cuando las condiciones de suelo a cada lado del mismo son diferentes. Con ello se logra mejorar la eficiencia y el control del vehículo, evitando posibles pérdidas de estabilidad que pueden resultar en riesgos para sus ocupantes. Tanto el observador como el control propuestos son diseñados en base a un modelo dinámico rotacional de la rueda y un modelo de fuerzas de brush. Se presentan resultados de simulación obtenidos empleando un modelo completo de vehículo sobre la plataforma Simulink/CarSim</p>