Browse Topic: Control systems

Items (5,558)
Electromobility is gaining importance in the courier, express and parcel (CEP) sector, as parcel service providers increasingly rely on zero-emission vehicles to improve their CO₂ footprint. A common drawback of battery electric vehicles is their reduced range under cold operating conditions, due to the increased energy demand for cabin heating. Another CEP-specific factor influencing both energy consumption and cabin comfort is the frequent opening of doors during parcel delivery. Additionally, during delivery phases, the cabin cools down in the driver’s repeated absence from the cabin, as the heating is inactive. Nonetheless, a sufficient level of thermal comfort must be maintained during the driving phases between delivery stops. This paper presents an optimization-based strategy for the cabin heating of battery electric CEP vehicles. The objective is to maximize cabin comfort during driving phases while maintaining efficient energy consumption. For this purpose, a nonlinear model
Rehm, DominikKrost, JonathanMeywerk, MartinCzarnetzki, Walter
Wind Tunnels are complex and cost-intensive test facilities. Thus, increasing the test efficiency is an important aspect. At the same time, active aerodynamic elements gain importance for the efficiency of modern cars. For homologation, such active aero-components pose an extra level of test complexity as their control strategies, the relevant drive cycles and their aerodynamics in different positions must be considered for homologation-relevant data. Often, active components have to be manually adjusted between test runs, which is a time-consuming process because the vehicle is not integrated into the test automation. Even if so, designing a test sequence stepping through the individual settings for each component of a vehicle is a tedious task in the test session. Thus, a sophisticated integration of the wind tunnel control system with a test management system, supporting the full homologation process is one aspect of a solution. The other is the integration of the vehicle’s active
Jacob, Jan D.
The road network is a critical component of modern urban mobility systems, with signalized traffic intersections playing a pivotal role. Traditionally, traffic light phase timings and durations at intersections are designed by transportation engineers using historical traffic data. Some modern intersections employ trigger-based mechanisms to improve traffic flow; however, these systems often lack global awareness of traffic conditions across multiple intersections within a network. With the increasing availability of traffic data and advancements in machine learning, traffic light systems can be enhanced by modeling them as agents operating in an environment. This paper proposes a Reinforcement Learning (RL) based approach for multi-agent traffic light systems within a simulation environment. The simulation is calibrated using real-world traffic data, enabling RL agents to learn effective control strategies based on realistic scenarios. A key advantage of using a calibrated simulation
Kalra, VikhyatTulpule, PunitGiuliani, Pio
In electric vehicles, the control of driveline oscillations and tire traction is critical for guaranteeing driver comfort and safety. Yet, achieving sufficient driveline control performance remains challenging in the presence of rapidly varying road conditions. Two promising avenues for further improving driveline control are adaptive model predictive control (MPC) and model-based reinforcement learning (RL). We derive such controllers from the same non-linear vehicle model and validate them through pre-defined test scenarios. The MPC approach employs input and output trajectory tracking with soft constraints to ensure feasible control actions even in the presence of constraint violations and is further supported by a Kalman filter for robust state estimation and prediction. In contrast, the RL controller leverages the model-based DreamerV3 algorithm to learn control policies autonomously, adapting to different road conditions without relying on external information. The results
Uhl, Ramón TaminoSchüle, IsabelLudmann, LaurinGeist, A. René
This research presents a semi-active suspension system that combines an air spring and a magneto-rheological (MR) fluid damper to produce both active force and variable damping rates based on the road conditions. The suspension system used for the military light utility vehicle (MLUV) has seven degrees of freedom. A nonlinear model predictive control system generates the desired active force for the air spring control signal, while the linear quadratic regulator (LQR) estimates the target tracking of the intended damping force. The recurrent neural network is designed to develop a controller for an identification system. To achieve the optimal voltage for the MR damper without log time, it is used to simultaneously determine the active control force of the air spring by modifying the necessary damping force tracking. The MLUV suspension system is integrated with the traction control system to improve overall vehicle stability. A fuzzy traction controller adjusts the throttle angle
Shehata Gad, Ahmed
This document applies to safety observers or spotters involved with the use of outdoor laser systems. It may be used in conjunction with AS4970.
G-10T Laser Safety Hazards Committee
The article introduces the air springs, CDC, rear-wheel steering system, braking system, front-wheel steering system, and electric drive system in the vehicle’s central coordinated motion control system. It explores achieving more comfortable shock absorption by adjusting the CDC (Continuously Variable Damping system) damping and other means. By combining open-loop and closed-loop rear-wheel steering control, the turning radius in small-radius steering mode is reduced by up to 10%, enabling crab-walking, optimizing the moose test entering speed up to 90.9 kph, and improving vehicle behavior on split-friction surfaces. Through the cooperation of IBS (Intelligent Brake System) and VMC, an extremely comfortable braking process is achieved.
Zhou, YuxingLi, Wen
This article introduces a comprehensive cooperative navigation algorithm to improve vehicular system safety and efficiency. The algorithm employs surrogate optimization to prevent collisions with cooperative cruise control and lane-keeping functionalities. These strategies address real-world traffic challenges. The dynamic model supports precise prediction and optimization within the MPC framework, enabling effective real-time decision-making for collision avoidance. The critical component of the algorithm incorporates multiple parameters such as relative vehicle positions, velocities, and safety margins to ensure optimal and safe navigation. In the cybersecurity evaluation, the four scenarios explore the system’s response to different types of cyberattacks, including data manipulation, signal interference, and spoofing. These scenarios test the algorithm’s ability to detect and mitigate the effects of malicious disruptions. Evaluate how well the system can maintain stability and avoid
Khan, Rahan RasheedHanif, AtharAhmed, Qadeer
This article aims to analyze and evaluate the roll safety thresholds (RSTs) and roll safety zones of tractor semi-trailer vehicles during turning maneuvers, using the roll safety factor (RSF) and yaw rate of the vehicle bodies. To achieve this, a full dynamics model is established using the multibody system method. This model is then used to survey and evaluate the vehicle’s motion state, using ramp steer maneuver (RSM) steering rules. In each survey case, the maximum values of RSF and yaw rate of vehicle bodies are synthesized in 3D data, with an initial velocity range of 40 km/h to 80 km/h and a magnitude of steering wheel angle range of 12.5° to 300°. These 3D data are used to determine the proposed values of RSF, which can be used as examples to set the threshold values of the yaw rate of vehicle bodies and roll safety zones. At a velocity of 60 km/h, the dynamic rollover threshold for proposed roll safety factor (RSFprop) is equal to 1, with corresponding values of 15.718°/s and
Hung, Ta Tuan
Public buses can be high-risk environments for the transmission of airborne viruses due to the confined space and high passenger density. However, advanced cabin air control systems and other measures can mitigate this risk. This research was conducted to explore various strategies aimed at reducing airborne particle transmission in bus cabins by using retrofit accessories and a redesigned parallel ventilation system. Public transit buses were used for stationary and on-road testing. Air exchange rates (ACH) were calculated using CO2 gas decay rates measured by low-cost sensors throughout each cabin. An aerosol generator (AG) was placed at various locations inside the bus and particle concentrations were measured for various experiments and ventilation configurations. The use of two standalone HEPA air filters lowered overall concentrations of particles inside the bus cabin by a factor of three. The effect of using plastic “barriers” independently showed faster particle arrival times
Lopez, BrendaSwanson, JacobDover, KevinRenck, EvanChang, M.-C. OliverJung, Heejung
To optimize vehicle chassis handling stability and ride safety, a layered joint control algorithm based on phase plane stability domain is proposed to promote chassis performance under complicated driving conditions. First, combining two degrees-of-freedom vehicle dynamics model considering tire nonlinearity with phase plane theory, a yaw rate and side slip angle phase plane stability domain boundary is drew in real time. Then based on the real-time stability domain and hierarchical control theory, an integrated control system with active front steering (AFS) and direct yaw moment control (DYC) is designed, and the stability of the controller is validated by Lyapunov theory. Finally, the lateral stability of the vehicle is validated by Simulink and CarSim simulations, real car data, and driving simulators under moose test and pylon course slalom test. The experimental results confirm that the algorithm can enhance the maneuverability and ride safety for intelligent vehicles.
Liao, YinshengZhang, ZhijieSu, AilinZhao, BinggenWang, Zhenfeng
To address the issue of intermittent engine intervention during the charging and discharging processes of hybrid vehicles, which results in roaring noise within the cabin, this paper proposes a semi-coupled cluster control strategy that offers superior overall performance. This strategy is based on the traditional multi-channel Active Noise Control (ANC) system and integrates the advantages of both centralized and decentralized control approaches. The proposed clustered control strategy reduces computational load by approximately 50% compared to the centralized control strategy, while maintaining comparable noise attenuation performance. Moreover, it demonstrates significantly improved stability over the decentralized control strategy, with outstanding noise reduction results. Using the MATLAB simulation platform, the performance of the proposed in-vehicle clustered control strategy is compared with that of traditional control strategies. Additionally, road test experiments are
Deng, HuipingLu, ChihuaChen, WanLiu, ZhienChen, PianDou, SiruiSun, Menglei
With the current popularity of new energy vehicles and the continuous development of intelligent cabin technology, the demand for acoustic comfort within automotive cockpit is increasing. A multi-channel feedforward active sound design and control method was proposed to improve the sound quality of the hybrid broadband road and narrowband order noise inside the test vehicle. The method selectively designed the target amplitudes for broadband noise and narrowband noise in the vehicle to satisfy passengers comfort, mainly including the sound design phase and the control phase. During the sound design phase, objective sound quality parameter analysis was first conducted on the noise of the prototype vehicle, followed by an subjective evaluation of the sound quality with rating scale method. An active acoustic design strategy focusing on comfort, motivation sense were proposed, including a formula for the target amplitude of adjustment order and sound pressure level. The sound quality was
Liu, XuexianXu, WenxuanLi, RubinLu, Lu
The segment manipulator machine, a large custom-built apparatus, is used for assembling and disassembling heavy tooling, specifically carbon fiber forms. This complex yet slow-moving machine had been in service for nineteen years, with many control components becoming obsolete and difficult to replace. The customer engaged Electroimpact to upgrade the machine using the latest state-of-the-art controls, aiming to extend the system's operational life by at least another two decades. The program from the previous control system could not be reused, necessitating a complete overhaul.
Luker, ZacharyDonahue, Michael
This article reviews the key physical parameters that need to be estimated and identified during vehicle operation, focusing on two key areas: vehicle state estimation and road condition identification. In the vehicle state estimation section, parameters such as longitudinal vehicle speed, sideslip angle, and roll angle are discussed, which are critical for accurately monitoring road conditions and implementing advanced vehicle control systems. On the other hand, the road condition identification section focuses on methods for estimating the tire–road friction coefficient (TRFC), road roughness, and road gradient. The article first reviews a variety of methods for estimating TRFC, ranging from direct sensor measurements to complex models based on vehicle dynamics. Regarding road roughness estimation, the article analyzes traditional methods and emerging data-driven approaches, focusing on their impact on vehicle performance and passenger comfort. In the section on road gradient
Chen, ZixuanDuan, YupengWu, JinglaiZhang, Yunqing
The wheel hub motor–driven electric vehicle, characterized by its independently controllable wheels, exhibits high torque output at low speeds and superior dynamic response performance, enabling in-place steering capabilities. This study focuses on the control mechanism and dynamic model of the wheel hub motor vehicle’s in-place steering. By employing differential torque control, it generates the yaw moment needed to overcome steering resistance and produce yaw motion around the steering center. First, the dynamic model for in-place steering is established, exploring the various stages of tire motion and the steering process, including the start-up, elastic deformation, lateral slip, and steady-state yaw. In terms of control strategy, an adaptive in-place steering control method is designed, utilizing a BP neural network combined with a PID control algorithm to track the desired yaw rate. Additionally, a control strategy based on tire/road adhesion ellipse theory is developed to
Huang, BinCui, KangyuZhang, ZeyangMa, Minrui
This document defines a set of standard application layer interfaces called JAUS Unmanned Ground Vehicle Services. JAUS Services provide the means for software entities in an unmanned system or system of unmanned systems to communicate and coordinate their activities. The Unmanned Ground Vehicle Services represent the platform-specific capabilities commonly found in UGVs, and augment the Mobilty Service Set [AS6009] which is platform-agnostic. At present ten (10) services are defined in this document. These services are categorized as:
AS-4JAUS Joint Architecture for Unmanned Systems Committee
Hybrid powertrain for motorcycles has not been widely adopted to date but has recently shown significant increased interest and it is believed to have great potential for fuel economy containment in real driving conditions. Moreover, this technology is suitable for the expected new legislations, reduced emissions and enables riding in Zero Emissions Zones, so towards a more carbon neutral society while still guaranteeing “motorcycle passion” for the product [1, 2]. Several simulation tools and methods are available for the concept phase of the hybrid system design, allowing definition of the hybrid components and the basic hybrid strategies, but they are not able to properly represent the real on-road behaviour of the hybrid vehicle and its specific control system, making the fine tuning and validation work very difficult. Motorcycle riders are used to expect instant significant torque delivery on their demand, that is not properly represented in legislative cycles (e.g. WMTC); rider
Antoniutti, ChristianSweet, DavidHounsham, Sandra
An implementation of a robust predictive cruise control method for class 8 trucks utilizing V2X communication with connected traffic lights is presented in this work. This method accounts for traffic signal phases with the goal of reducing energy consumption when possible while respecting safety concerns. Tightened constraints are created using a robust model predictive control (RMPC) framework in which constraints are modified so that the safety critical requirements are satisfied even in the presence of disturbances, while requiring only the expected bounds of the disturbances to be provided. In particular, variation in the actuator performance under different conditions presents a unique challenge for this application, which the approach applied in this work is well-suited to handle. The errors resulting from lower-level control and actuator performance are accounted for by treating them as bounded and additive disturbances on the states of the model used in the higher level MPC
Ellison, EvanWard, JacobBrown, LowellBevly, David M.
Model-based developers are turning to DevOps principles and toolchains to increase engineering efficiency, improve model quality and to facilitate collaboration between large teams. Mature DevOps processes achieve these through automation. This paper demonstrates how integrating modern version control (Git) with collaborative development practices and automated quality enforcement can streamline workflows for large teams using Simulink. The focus is on enhancing model consistency, enabling team collaboration, and development speed.
Mathews, JonTamrawi, AhmedFerrero, SergioSauceda, Jeremias
In a conventional cam-based valve actuation system, the valve events are tied up with the rotation of the crankshaft. In contrast, the electronic variable valve actuation (VVA) system enables flexible control of valve events independent of the crankshaft rotation. The present article discusses the development and control system design of a single-acting electro-pneumatic variable valve actuation (EPVVA) system that can be retrofitted to a conventional SI engine. The EPVVA system utilizes fast switching solenoid valves which modulate the flow of pressurized air in and out of a pneumatic chamber. The control system design is conducted in MATLAB Simulink platform using model-based approach. The valve actuator model is formulated such that it simulates the trajectory of the motion of the engine valve by numerically integrating a set of coupled differential equations that govern the thermo-fluid-dynamics and applied mechanics aspects of the valve actuation of the EPVVA system. The timings
Satalagaon, Ajay KumarGuha, AbhijitSrivastava, Dhananjay Kumar
Motor drive control is crucial for achieving the performance, reliability, and comfort of electric vehicles. Multi-phase motors, represented by dual-winding permanent magnet synchronous motors (PMSMs), have significant research value in the electric vehicle field due to their high-power drive capabilities and strong fault tolerance. A simple and easily analyzable motor model is essential for achieving high precision in control. This paper employs VSD coordinate transformation (vector space decomposition) based on electromagnetic principles and the positional relationships between windings, treating the multi-phase motor as a whole and mapping various physical quantities to multiple subspaces for simplified analysis. Consequently, a mathematical model for the dual-winding PMSM is established. The vector control system based on VSD coordinate transformation adopts a dual closed-loop structure for speed and current. It focuses on a comparative analysis between traditional two-vector
Gao, ChaoFanZheng, HongyuKaku, Chuyo
Improving the efficiency of Battery Electric Vehicles (BEVs) is crucial for enhancing their range and performance. This paper explores the use of virtual tools to integrate and optimise various systems, with a particular focus on thermal management. The study considers global legislative drive cycles and real-world scenarios, including hot and cold weather conditions, charging cycles, and towing. A virtual vehicle model is developed to include major contributors to range prediction and optimisation, such as thermal systems. Key components analysed include high voltage (HV) and low voltage (LV) consumers (compressors, pumps, fans), thermal system performance and behaviour (including cabin climate control), thermal controllers, and thermal plant models. The emergent behaviour resulting from the interaction between hardware and control systems is also examined. The methodology involves co-simulation of hardware and control models, encompassing thermal systems (coolant, refrigerant, cabin
Tourani, AbbasPrice, ChristopherDutta, NilabzaMoran Ruiz, Eduardo
This paper presents a comparative study between many control techniques to investigate the efficiency of the path tracking in various driving scenarios. In this study the Model predictive control (MPC), the adaptive model predictive control (AMPC) and the Stanley controller are employed to ensure that the vehicle follows reference paths accurately and robustly under varying environmental and vehicular conditions. Two driving scenarios are utilized S-road and Curved-road with MATLAB/Simulink under three different vehicle speeds to investigate vehicle performance employing the root mean square error (RMSE) as the performance evaluation function. Particle swarm optimization (PSO) utilized for optimizing the six parameters of the MPC prediction horizon (P), Control horizon(m), manipulated variable rates, manipulated variables weights and two output variables weights. Four objective functions are employed with PSO and compared to each other in terms of the time domain regarding the RMSE of
Eldesouky, Dina M.MustafaAbdelaziz, Taha HelmyMohamed, Amr.E
Accurate estimation of the state of charge (SoC) of battery cells is crucial for the efficient management and longevity of battery systems, particularly in electric vehicles and renewable energy storage. This paper presents an approach utilizing a nonlinear autoregressive exogenous (NARX) model to estimate the SoC of battery cells. The proposed method leverages hyperparameter optimization to determine the optimal configuration of the neural network, including the number of neurons, the number of hidden layers, the number of feedback loops, the best activation function, and the most effective learning rate. The primary objective of this research is to minimize the estimation error of the SOC to within 2%, thereby enhancing the reliability and performance of battery management systems. The hyperparameter optimization process involves a systematic search and evaluation of various configurations to identify the most effective neural network architecture. This process is critical as it
Saini, SandeepAdmane, Chinmay
This paper initially delineates the control process of driver-initiated gear changes. The gear-shifting point control module computes the new target gear based on the current updated driving state, and the gear-shifting point decision module assesses the rationality of the new target gear and conveys it to the gear-shifting timing control module. The gear-shifting timing control module selects the reasonable new stage in accordance with the current execution status and outputs the new target gear, coordinating the clutch control module and the brake control module to regulate the clutch engagement/disengagement and the switches of the two clutches. Altering the intention regarding gear changes encompasses gear replacement and variations in power type, which involve the necessary recalculation of the target speed based on the new target gear. Secondly, the conditions for the “change of mind” request in the speed stage are stipulated, which is the stage where the input shaft speed is
Jing, JunchaoHuang, WeishanLi, DongfeiZuo, BotaoLiu, Yiqiang
Adverse weather conditions such as rain and snow, as well as heavy load transportation, can cause varying degrees of damage to road surfaces, and untimely road maintenance often results in potholes. Perception sensors equipped on intelligent vehicles can identify road surface conditions in advance, allowing each wheel’s suspension to actively adjust based on the road information. This paper presents an active suspension control strategy based on road preview information, utilizing a newly designed dual-chamber active air suspension system. It addresses the issue of point cloud stratification caused by vehicle body vibrations in onboard LiDAR data. The point cloud is processed through segmentation, filtering, and registration to extract real-time road roughness information, which serves as preview information for the suspension control system. The MPC algorithm is applied to actively adjust the nonlinear stiffness and damping of the suspension’s dual-chamber air springs, enhancing
Dong, FuxinShen, YanhuaWang, KaidiLiu, ZuyangQian, Shuo
Trajectory tracking control is a critical component of the autopilot system, essential for achieving high-performance autonomous driving. This paper presents the design of a stable, reliable, accurate, fast, and robust trajectory tracking controller. Specifically, a lateral and longitudinal trajectory tracking controller based on a linear parameter time-varying model predictive control (LPV-MPC) framework is designed. Firstly, a three-degree-of-freedom vehicle dynamics model and a tracking error model are established. Secondly, a multi-objective function and constraints considering tracking accuracy and lateral stability are formulated, and the quadratic programming (QP) method is employed to solve the optimization problem. Finally, PID speed tracking control is introduced in the longitudinal control scheme for comparison with the proposed MPC longitudinal speed control. A step velocity tracking test validates the effectiveness of the MPC speed tracking controller. In the lateral
Pan, ShicongLu, JunYu, YinquanZeng, DequanYang, JinwenHu, YimingJiang, ZhiqiangLiu, Dengcheng
Distributed electric vehicles, equipped with independent motors at each wheel, offer significant advantages in flexibility, torque distribution, and precise dynamic control. These features contribute to notable improvements in vehicle maneuverability and stability. To further elevate the overall performance of vehicles, particularly in terms of handling, stability, and comfort, this paper introduces an coordinated control strategies for longitudinal, lateral, and vertical motion of distributed electric vehicles. Firstly, a full-vehicle dynamics model is developed, encompassing interactions between longitudinal, lateral, and vertical forces, providing a robust framework for analyzing and understanding the intricate dynamic behaviors of the vehicle under various operating conditions. Secondly, a vehicle motion controller based on Model Predictive Control is designed. This controller employs a sophisticated multi-objective optimization algorithm to manage and coordinate several critical
Jia, JinchaoYue, YangSun, AoboLiu, Xiao-ang
As the complexity of electrified powertrains and their architectures continue to grow and thrive, it becomes increasingly important and challenging for the supervisory torque controller to optimize the torque commands of the electric machines. The hybrid architecture considered in this paper consists of an internal combustion engine paired with at least one electric motor and a DC-DC switching converter that steps-up the input voltage, in this case the high voltage battery, to a higher output voltage level allowing the electric machines to operate at a greater torque range and increased torque responsiveness for efficient power delivery. This paper describes a strategy for computing and applying the losses of the converter during voltage transformation to determine the optimal engine and electric motor torque commands. The control method uses a quadratic fit of the losses at the power limits of the torque control system and on optimal motor torque commands, within the constraints of
Venkataramu, AchyutWalsh, McKenzieTischendorf, ChristophSullivan, MaryPatel, NadirshHuo, ShichaoSharma, Ashay
Toyota Motor Corporation pursuing an omnidirectional strategy that includes battery electric vehicle (BEV), plug-in hybrid electric vehicle (PHEV), and fuel cell electric vehicle (FCEV) to accelerate electrification. One of the technical challenges with our xEV batteries which feature good degradation resistance and long battery life, is that regenerative braking cannot be fully effective due to the decrease in regenerative power in some situations, such as low battery temperature. For the electrified vehicles with an internal combustion engine such as PHEVs, the solution has been running the engine to increase deceleration through engine braking during coasting. PHEVs are expected to extend their cruising range and enhance EV driving experience as "Practical BEVs". While increasing battery capacity and enhancing convenience, the restrictions on EV driving opportunity due to low battery temperature may negatively affect PHEV’s appealing. As an alternative, introducing a battery heater
Hoshino, Yu
Advanced driver assistance systems (ADASs) and driving automation system technologies have significantly increased the demand for research on vehicle-state recognition. However, despite its critical importance in ensuring accurate vehicle-state recognition, research on road-surface classification remains underdeveloped. Accurate road-surface classification and recognition would enable control systems to enhance decision-making robustness by cross-validating data from various sensors. Therefore, road-surface classification is an essential component of autonomous driving technologies. This paper proposes the use of tire–pavement interaction noise (TPIN) as a data source for road-surface classification. Traditional approaches predominantly rely on accelerometers and visual sensors. However, accelerometer signals have inherent limitations because they capture only surface profile properties and are often distorted by the resonant characteristics of the vehicle structure. Similarly, image
Yoon, YoungsamKim, HyungjooLee, Sang KwonLee, JaekilHwang, SungukKu, Sehwan
The electric vehicle market, vehicle ECU computing power, and connected electronic vehicle control systems continue to grow in the automotive industry. The results of these advanced and expanded vehicle technologies will provide customers with increased cost savings, safety, and ride quality benefits. One of these beneficial technologies is the tire wearing prediction. The improved prediction of tire wear will advise a customer the best time to change tires. It is expected that this prediction algorithms will be essential part for both the optimization of the chassis control systems and ADAS systems to respond to changed tire performance that varies with a tire’s wear condition. This trend is growing, with many automakers interested in developing advanced technologies to improve product quality and safety. This study is aimed at analyzing the handling and ride comfort characteristics of the tire according to the depth of tire pattern wear change. The handing and ride comfort
Kim, ChangsuKwon, SeungminSung, Dae-UnRyu, YonghyunKo, Younghee
In order to improve the safety and reliability of the inverter used in hybrid vehicles and reduce the risk of inverter failure, based on the functional safety ISO26262 development process and software architecture, a safe shutdown path scheme is designed in this paper. Firstly, after entering the initialization mode, on the basis of adding the inverter control signal feedback mechanism on the inverter control system, this scheme designs the control methods and specific processes of the shutdown path test and insulation detection. The shutdown path test and insulation detection designed in this scheme are implemented during the control initialization process, including designing the hardware diagnostic safety mechanism and the unique output shutdown path test method. If the shutdown path test or insulation detection fails, the risk of IGBT out of control can be avoided; the detection mechanism of this system can effectively reduce the failure rate and potential failure rate of faults
Jing, JunchaoLiu, YiqiangZuo, BotaoHuang, WeishanDai, Zhengxing
Clamping force control in Electromechanical Brake (EMB) systems must overcome various nonlinear characteristics, such as motor distorted voltage, Back Electromotive Force (EMF), and actuator friction disturbances. Therefore, modeling and parameter identification of these nonlinearities are necessary. This paper first proposes a motor parameter identification method based on the mathematical model of a Permanent Magnet Synchronous Motor (PMSM). A combination of the Least Square Method and Particle Swarm Optimization (PSO) is used to stepwise identify both the electrical and mechanical parameters of the motor. The accuracy of the identified parameters is validated by comparing simulation results with test bench responses. The identified parameters are applied to design the motor Back EMF compensation module, the distorted voltage compensation module, and to tune the current loop parameters. Next, a lumped parameter friction model suitable for closed-loop clamping force control in EMB
Qiao, LeXiong, LuZhuo, GuirongShu, Qiang
Online road profiling capability is required for automotive active suspension systems to be realized in a consumer and commercial landscape. One challenge that impedes the realization of these systems is the need for the online road profiler to maintain an optimal spatial resolution of the oncoming road profile. Shifting of the road profiling sensor measurement frame of reference due to body motion experienced by the vehicle can negatively impact profiling accuracy. Prior work proposed a corrective look-ahead road profiling system (CLARPS) and demonstrated the CLARPS architecture and initial MATLAB/Simulink simulation environment. First, this work further develops the robust simulation environment. The simulation allows the look-ahead viewing angles to be optimized for the best road profile spatial resolution and facilitates a study on the impact of road profiler sensor location on the accuracy of the generated road profile. Second, this work introduces a lab-scale physical CLARPS
Morison, DaneMynderse, James
The motor controller, as one of the important controllers in the electric drive system, may cause unexpected acceleration or deceleration of the vehicle by the driver due to systematic failure and random hardware failure. Conducting research on the functional safety of drive motors for new energy vehicles is of great significance for reducing the systematic failure and random hardware failure of the electric drive. This paper has carried out designs including the allowable motor torque design for safety monitoring, the motor torque prediction design for safety monitoring, the rationality judgment design of the motor torque for safety monitoring, the rationality judgment design of the motor direction for safety monitoring, the functional safety motor degradation design, and the active discharge state monitoring of the motor, so that the system can transition to a safe state when an error occurs. Among them, the motor torque prediction design for safety monitoring includes predicting the
Jing, JunchaoZuo, BotaoLiu, YiqiangHuang, WeishanDai, Zhengxing
In future planetary exploration missions, the Eight-Wheeled Planetary Laboratory (EWPL) will have sufficient capacity for tasks but will experience significant lateral slips during high-speed turns due to its large inertia. Modern technology allows for independent steering of all eight wheels, but controlling each wheel's steering angle is key to improving stability during turns. This paper introduces a novel rear-axle steering feed-forward controller to reduce sideslip. First, a mathematical model for the vehicle's steering is established, including kinematic equations based on Ackermann steering. Feed-forward zero side-slip control is applied to the third and fourth axles to counteract the side-slip angle of the center of mass. A multi-body dynamics model of the EWPL is then built in Chrono to evaluate the turning radius and optimize steering angle ratios for the rear axles. Finally, a steady-state cornering simulation on loose terrain compares the performance of the proposed
Liu, JunZhang, KaidiShi, JunweiYang, WenmiaoZhang, YunqingWu, Jinglai
Because the steer-by-wire (SBW) system cancels the mechanical connection between the steering wheel and the steering wheel in the traditional mechanical steering system (MSS), various road information on the road cannot be directly transmitted to the driver through the steering wheel in the form of road sense. Consequently, drivers are unable to genuinely perceive this road information, which adversely affects their control of the vehicle. This paper investigates the road perception simulation method for SBW systems. Initially, a dynamic model of the SBW system is developed, and its validity is confirmed under conditions of step changes in steering wheel angle and dual-shifting scenarios. A state estimation approach is employed to simulate road perception torque, and a corresponding torque calculation formula is derived based on the dynamic model of traditional steering systems. A two-degree-of-freedom vehicle model is constructed to independently compute the lateral force experienced
Li, XuesongLi, ZhichengZheng, HongyuKaku, Chuyo
As longitudinal Automated Driving System (ADS) technologies, such as Adaptive Cruise Control (ACC), become more prevalent, robust testing frameworks that encompass both simulation and vehicle-in-the-loop (VIL) methodologies are essential to ensure system reliability, safety, and performance refinement. Although significant research has focused on ACC algorithm development and simulation testing, existing VIL dynamometer testing frameworks are typically tailored to specific vehicle models and sensor simulation tools. These highly customized approaches often fail to account for broader interoperability while overlooking energy consumption as a key performance metric. This paper presents a novel modular framework for ACC dynamometer testing, designed to enhance interoperability across a diverse range of vehicle platforms, simulation tools, and dynamometer facilities with a focus on evaluating impacts of automated longitudinal control on the overall energy consumption of the vehicle. The
Goberville, NicholasHamilton, KaylaDi Russo, MiriamJeong, JongryeolDas, DebashisOrd, DavidMisra, PriyashrabaCrain, Trevor
The electric motor is a significant source of noise in electric vehicles (EVs). Traditional hardware-based NVH optimization techniques can prove insufficient, often resulting in trade-offs between motor torque or efficiency performance. The implementation of motor control-based torque ripple cancellation (TRC) technology provides an effective and flexible solution to reduce the targeted orders. This paper presents an explanation of the mathematical theory underlying the TRC method, with a particular focus on the various current injection methods, including those that allow up to 4DOFs (degrees-of-freedom). In the case study, the injection of controlled fifth or seventh order current harmonics into a three-phase AC motor is shown to be an effective method for cancelling the most dominant sixth order torque ripple. A dedicated feedforward harmonic current generation module is developed the allows the application of harmonic current commands to a motor control system with adjustable
He, SongGong, ChengChang, LePeddi, VinodZhang, PengGSJ, Gautam
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