Browse Topic: Control systems
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.
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
This paper presents an advanced control system design for an engine cooling system in an internal combustion engine (ICE) vehicle. Building upon our previous work, we have derived models for crucial temperatures within the engine, including combustion wall temperature, coolant-out temperature, block temperature, as well as temperatures in external components such as heat exchangers and radiator. To accurately predict these temperatures in a rapid manner, we have utilized a lumped parameter concept with a mean-value approach. This approach allows for precise temperature estimation while maintaining computational efficiency. Given the complexity of the cooling system, we have proposed a linear time-varying (LTV) model predictive control (MPC) system to regulate the temperatures. This control system linearizes the model at each time step and applies linear MPC over the control and prediction horizons. By doing so, we effectively control the highly nonlinear and time-delayed system
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
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
Abstract Real-world driving data is an invaluable asset for several types of transportation research, including emissions estimation, vehicle control development, and public infrastructure planning. Traditional methods of real-world driving data collection use expensive GPS-based data logging equipment which provide advanced capabilities but may increase complexity, cost, and setup time. This paper focuses on using the Google Maps application available for smartphones due to the potential to scale-up real-world driving data logging. Samples of the potential data processing and information that can be gathered by such a logging methodology is presented. Specifically, two months of Google Maps driving data logged by a rural Michigan resident on their smartphone may provide insights on their driving range, duration, and geographic area of coverage (AOC) to guide them on future vehicle purchase decisions. Aggregating such statistics from crowd-sourcing real-world driving data via Google
Autonomous vehicles utilise sensors, control systems and machine learning to independently navigate and operate through their surroundings, offering improved road safety, traffic management and enhanced mobility. This paper details the development, software architecture and simulation of control algorithms for key functionalities in a model that approaches Level 2 autonomy, utilising MATLAB Simulink and IPG CarMaker. The focus is on four critical areas: Autonomous Emergency Braking (AEB), Adaptive Cruise Control (ACC), Lane Detection (LD) and Traffic Object Detection. Also, the integration of low-level PID controllers for precise steering, braking and throttle actuation, ensures smooth and responsive vehicle behaviour. The hardware architecture is built around the Nvidia Jetson Nano and multiple Arduino Nano microcontrollers, each responsible for controlling specific actuators within the drive-by-wire system, which includes the steering, brake and throttle actuators. Communication
The Tractor is essential in both agriculture and construction, equipped with a variety of implements for different operational conditions. Its hydraulic system is crucial for controlling these implements during fieldwork and transport. The quadrant assembly is a key part of the tractor’s hydraulic control system, allowing the operator to manage important functions. This includes hydraulic control and draft control, enabling the farmer or operator to use the PC and DC levers to adjust the movement of implements during various tasks. Tractors are commonly used in fields and farms where the soil can be loose and muddy, particularly during wet puddling operations. In these muddy conditions, tractors can accumulate mud in critical components, such as the quadrant assembly. This can lead to functional issues, increased friction, and problems within the hydraulic system, especially affecting the controls for hydraulics and lever shifting for implement handling. As a result, operators may need
PEM electrolysis system has characteristic of excellent performance such as fast response, high electrolysis efficiency, compact design and wide adjustable power range. It provides a sustainable solution for the production of hydrogen, and is well suited to couple with renewable energy sources. In the development process of PEM electrolysis controller, this article originally applied the V-mode development process, including simulation modeling, RCP testing, and HIL testing, which can provide guidance in the practical application of electrolytic hydrogen production. In this paper, we present modeling and simulation study of PEM water electrolysis system. Model of electrolytic cell, hydrogen production subsystem and thermal management subsystem are constructed in Matlab/Simulink. Controller model was designed based on PI control strategy. A rapid prototyping controller with MPC5744 chip was used to develop the control system of electrolytic hydrogen production system. Hardware in the
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