Browse Topic: Adaptive control
One of the challenges of Electric Vehicles (EVs) is to provide thermal comfort for the occupants while minimizing the energy consumption and the impact on the driving range. Conventional heating systems, such as Positive Temperature Coefficient (PTC) heaters, consume a large amount of battery power and reduce the efficiency of the EVs. Heat Pumps (HPs) are an alternative heating system that can divert heat from the ambient air and transfer it to the cabin. HPs can achieve higher Coefficient of Performance (COP) than PTC heaters and save energy. However, for Indian sub-continent conditions HPs have some drawbacks, such as low heating capacity at low ambient temperatures, and variable performance depending on the operating conditions. Therefore, it is important to design and control the HP system optimally. This study employs 1D Computer-Aided Engineering (CAE) modelling and simulation techniques to analyse the performance of heat pump systems within the confined environment of an EV
This SAE Recommended Practice establishes uniform procedures for assuring the manufactured quality, installed utility, and service performance of manual automotive adaptive products, other than those provided by the OEM, intended to provide driving capability for persons with physical disabilities. These devices function as adaptive appliances to compensate for lost or reduced performance in the drivers’ arms or legs, or both. Some of the devices are designed to transfer foot functions to the hands, hand functions to the feet, or functions from one side of the body to the other. This document applies only to primary controls as defined in 3.4.1 and in the Foreword. In particular, this document is specifically concerned with those mechanical and hybrid products that are intended by the manufacturer of the adaptive product to: Be installed within the occupant space of the vehicle Be operated by a vehicle driver with a physical disability Be added to, or substituted for, the OEM vehicle
This research aims to develop an inverse controller to track target vibration signals for the application to car subsystem evaluations. In recent times, perceptive assessments of car vibration have been technically significant, particularly parts interacting with passengers in the car such as steering wheels and seats. Conventional vibration test methods make it hard to track the target vibration signals in an accurate manner without compensating for the influence of the transfer function. Hence, this paper researched the vibration tracking system based on inverse system identification and digital signal processing technologies. Specifically, the controller employed a semi-active algorithm referring to both the offline modeling of the inverse system and the adaptive control. The semi-active controller could reconstruct the target vibration signal in a more efficient and safer way. The proposed methodology was first confirmed through computation simulations using Simulink. The
The paper presents a robust adaptive control technique for precise regulation of a port fuel injection + direct injection (PFI+DI) system, a dual fuel injection configuration adopted in modern gasoline engines to boost performance, fuel efficiency, and emission reduction. Addressing parametric uncertainties on the actuators, inherent in complex fuel injection systems, the proposed approach utilizes an indirect model reference adaptive control scheme. To accommodate the increased control complexity in PFI+DI and the presence of additional uncertainties, a nonlinear plant model is employed, incorporating dynamics of the exhaust burned gas fraction. The primary objective is to optimize engine performance while minimizing fuel consumption and emissions in the presence of uncertainties. Stability and tracking performance of the adaptive controller are evaluated to ensure safe and reliable system operation under various conditions. Simulation studies demonstrate the reliability and
Aurora Flight Sciences, a Boeing Company Manassas, VA 703-369-3633
Vehicles-to-Everything or V2X communications provide attractive advantages in achieving reliable and high-performance connectivity amongst ground and aerial military vehicles. The 5G New Radio (NR) based cellular-V2X (C-V2X) technology, can support wide coverage areas with higher data rates and lower latencies needed for demanding military applications ranging from real-time sensing to navigation of autonomous military ground vehicles. Millimeter wave technology (mmWave) is critical to meet such throughput and latency requirements. However, mmWave links have a low transmission range and are often subject to blockages due to factors like weather, terrain, etc. that make them unreliable. Multi-connectivity with packet duplication can be used to enhance the reliability and latency by transmitting concurrently over independent links between a mobile device and multiple base stations. We propose and evaluate a novel method based on new radio dual connectivity (NR-DC) and packet duplication
An integrated electrically heated catalyst (EHC) in the three-way catalyst (TWC) of a gasoline internal combustion engine (ICE) is a promising technology to reduce engine cold-start pollutant emissions. Pre-heating the TWC ensures earlier catalyst light-off of a significant portion of the TWC. In such a case, the engine could readily be operated in a fuel-optimal manner since the engine cold-start emission is efficiently treated by the warmed-up EHC-equipped TWC. Pre-heating the EHC is an effective way to reduce cold-start emissions, among other possible EHC strategies. However, it might not always be possible to use pre-heating if the engine-start time is uncertain. In such a case, pre-heating can be started when the engine start is known with greater confidence and post-heating the catalyst could be followed. It would then be natural to turn off the EHC when the payoff for the electrical energy spent is no longer effective in engine cold-start emission reduction. The point in time at
Lateral control is an important part in the system of driverless mining trucks, which is used to realize accurate tracking of planned path. To solve the problem of poor accuracy of the existing single point preview algorithm, firstly, the lateral error model and the simplified truck dynamics model were built. The established truck dynamics model was verified and compared by simulation. The results show that the truck dynamic model in this paper retains accurate even at higher speed. Secondly, against the time delay of truck steering system, the cascade LQR-PID controller and MPC-MRAC controller are designed. The former resists the disturbance of steering time delay through the inner PID loop, while the latter realizes the adaptive control by establishing the steering model. Then, the dual-shift condition simulation was carried out by co-simulation model, and two controllers were compared and analyzed. The results show that the designed two controllers have good performance in the
Humanity has been interested in magnetism for over 300 years. Many authors have studied the use of applied magnetism to change the properties of products and expand the use of magnetic processing in ship repair production [1, 2]. Experience shows that magnetic pulse processing (MPP) is a simple and economical way to increase the durability of metal-cutting tools, increase the resource of the most worn parts of machines and mechanisms, and increase the durability of friction units, assembly units, and structures during their repair and manufacture. MPP has a number of advantages: simplicity of electromagnetic energy concentration on the product, its rapid accumulation by the material of the working elements of the part, and the efficiency of improving the operational characteristics (processing time is 0.3 ... 2.0 s with insignificant energy consumption). The indicated advantages of magnetic processing of products in comparison with other methods of hardening have been repeatedly
With increasing requirements for small engines in terms of functionalities and emission standards, it is essential to be able to offer an integrated full-featured injection system that will meet future requirements. The system described is particularly suitable for small to medium-sized combustion engines, such as power generators, lawnmowers and small motorcycles, and has a corresponding cost structure, compactness and a high degree of integration. The main subject of the development is an electronic fuel injection system, which can provide information about the current air-fuel mixture through model-based software algorithms and also has an integrated ignition coil. This article describes the procedure and the status of the research results of this development project. The basis of the method as already known from similar approaches of stimulating the running engine by a defined feedforward control of the injection quantity. The engine response is analyzed by the developed algorithm
This project seeks to reproduce the neural circuits used by the nematode Caenorhabditis elegans for locomotion. Caenorhabditis elegans is a small (~1.2 millimeter) nematode found in rotting fruit in many parts of the world. It feeds on bacteria and is neither parasitic nor pathogenic. Although capable of sexual reproduction, most laboratory strains reproduce primarily as self-fertilizing hermaphrodites, with each adult hermaphrodite producing approximately 300 progeny (Figure 1
Agricultural tractors are often subjected to various applications like front end loading work, cultivation work, where frequent forward and reverse gears are needed. Most of Indian agricultural tractors are equipped with mechanical transmission system which demands repeated clutching and de-clutching operation for such applications resulting in increased operator fatigue and lesser productivity. Also need of electronics in Indian agricultural industry for better farm mechanization is growing high. This research work depicts development of electronic bi-directional shifting (power shuttle) control design and calibration for farm vehicle fitted with wet clutch transmission. This research also reduces operator fatigue via frequent directional shift through electronic transmission. The control system is designed without any electronic interfacing with engine and also provides clutch-less gear shifting and auto-launch which offers ease to drive even for novice driver. The power shuttle
Government regulations for fuel economy and emission standards have driven the development of technologies that improve engine performance and efficiency. These technologies are enabled by an increased number of actuators and increasingly sophisticated control algorithms. As a consequence, engine control calibration time, which entails sweeping all actuators at each speed-load point to determine the actuator combination that meets constraints and delivers ideal performance, has increased significantly. In this work we present two adaptive optimization methods, both based on an indirect adaptive control framework, which improve calibration efficiency by searching for the optimal process inputs without visiting all input combinations explicitly. The difference between the methods is implementation of the algorithm in steady-state vs dynamic operating conditions. The goal of this work is to study the optimization performance tradeoffs between robustness to sensor noise and required
With the trending electrification of vehicle accessory drives brings new control concepts useful in many cases to optimize energy management within the powertrain system. Considering that direct engine drives do not have as much flexibility as independent electric drives, it is apparent that several advantages are to be expected from electric drives. New developed high efficient electric drives can be implemented when considering many vehicle sub-systems. Combinations of continuous varying and discrete flow control devices offer thermal management opportunities across several vehicle attributes including fuel economy, drivability, performance, and cabin comfort. Often new technologies are integrated with legacy systems to deliver maximum value. Leveraging both electrical and mechanical actuators in some cases presents control challenges in optimizing energy management while delivering robust system operation. In this paper Electrification of Water Cooling Pump has been considered where
A new lateral stability control method, which is based on vehicle sideslip angle and tire cornering stiffness estimation, is proposed to improve the lateral stability of the four-in-wheel-motor-driven electric vehicle (FIWMD-EV) in this paper. Through the lateral tire force information, vehicle sideslip angle can be estimated by the extended kalman filter (EKF). Using the estimated vehicle sideslip angle, tire cornering stiffness can be also estimated by forgetting factor recursive least squares (FFRLS). Furthermore, combining with the vehicle dynamics model, an adaptive control target model is proposed with the information on vehicle sideslip angle and tire cornering stiffness. The new lateral stability control system uses the direct yaw moment control (DYC) based on dynamic sliding mode is proposed. The performance and effectiveness of the proposed vehicle state estimation and lateral stability control system are verified by CarSim and Simulink cosimulation. Comparing with the
A team of scientists from the University of Virginia (UVA) School of Medicine and the Harvard John A. Paulson School of Engineering and Applied Sciences developed a project to turn an ordinary smartphone into an artificial pancreas that has since received a $3.4 million grant from the National Institutes of Health. Now, researchers are beginning one of the largest-ever long-term clinical trials of a system designed to help regulate blood sugar levels of individuals with type 1 diabetes mellitus. The “artificial pancreas” system will be tested in 240 patients at nine sites in the US and Europe. Two six-month trials are beginning in early 2016, in collaboration with a half dozen other institutional partners
Hybrid electric vehicles offer significant fuel economy benefits, because battery and fuel can be used as complementing energy sources. This paper presents the use of dynamic programming to find the optimal blend of power sources, leading to the lowest fuel consumption and the lowest level of harmful emissions. It is found that the optimal engine behavior differs substantially to an on-line adaptive control system previously designed for the Lotus Evora 414E. When analyzing the trade-off between emission and fuel consumption, CO and HC emissions show a traditional Pareto curve, whereas NOx emissions show a near linear relationship with a high penalty. These global optimization results are not directly applicable for online control, but they can guide the design of a more efficient hybrid control system
As combustion can vary widely between engine cycles if left uncontrolled, strict and robust control is required to meet optimum performance at different operating conditions. In this research, intelligent control techniques implemented on a Gasoline Direct Compression Injection (GDCI/GDI) engine. A research four cylinder 2.0 L GDI engine modeled with optimal control hardware that is frequently called as the conceptual Cybernetic intelligent GDI or ‘iGDI’ engine. The engine features Free Valve Actuation (FVA) hardware and precision fuel injector connected directly to the engine cylinder that found assistive for control flexibility by technical assessments. Then a mechatronic neural control approach is proposed and discussed with adaptive control techniques. Adaptive and predictive neural network control architectures developed for two distinct plant operation modes. The engine and the controllers are modeled and simulated with GT-SUITE and SIMULINK coupled simulation for control
This paper proposes a model reference adaptive control (MRAC) strategy for active trailer steering (ATS) in order to improve the lateral stability of articulated heavy vehicles (AHVs). Optimal controllers based on the Linear Quadratic Regulator (LQR) technique have been explored to enhance the lateral stability of AHVs; these controllers are designed under the assumption that the vehicle model parameters and operating conditions are given and they remain as constants. However, in reality, the vehicle system parameters and operating conditions may vary. To address the variable payloads of trailer(s), the controller based on MRAC technique is adopted. A three degrees of freedom (DOF) linear yaw-plane tractor-semitrailer model is generated to design the control law. The reference model is also developed using the linear yaw-plane model with the LQR technique. The effectiveness of the MRAC controller is demonstrated using numerical simulations under an emulated single lane-change maneuver
The passive fault-tolerant approach for four-wheel independently driven and steered (4WID/4WIS) electric vehicles has been investigated in this study. An adaptive control based passive fault-tolerant controller is designed to improve vehicle safety, performance and maneuverability when an actuator fault happens. The proposed fault tolerant control method consists of the following three parts: 1) a fault detection and diagnosis (FDD) module that monitors vehicle driving condition, detects and diagnoses actuator failures with the inequality constraints; 2) a motion controller that computes the generalized forces/moments to track the desired vehicle motion using Model Predictive Control (MPC); 3) a reconfigurable control allocator that redistributes the generalized forces/moments to four wheels with equality constrained optimization. The FTC approach is based on the reconfigurable control allocation which reallocates the generalized forces/moments among healthy actuators once the actuator
Diesel Particulate Filters (DPF) are a key component in many on- and off-road aftertreatment systems to meet increasingly stringent particle emissions limits. Efficient thermal management and regeneration control is critical for reliable and cost-effective operation of the combined engine and aftertreatment system. Conventional DPF control systems predominantly rely on a combination of filter pressure drop measurements and predictive models to indirectly estimate the soot loading state of the filter. Over time, the build-up of incombustible ash, primarily derived from metal-containing lubricant additives, accumulates in the filter to levels far exceeding the DPF's soot storage limit. The combined effects of soot and ash build-up dynamically impact the filter's pressure drop response, service life, and fuel consumption, and must be accurately accounted for in order to optimize engine and aftertreatment system performance. This work applied a radio frequency (RF) sensor to directly
The 30 month COMET project aims to overcome the challenges facing European manufacturing industries by developing innovative machining systems that are flexible, reliable and predictable with an average of 30% cost efficiency savings in comparison to machine tools. From a conceptual point of view, industrial robot technology could provide an excellent base for machining being both flexible and cost efficient. However, industrial robots lack absolute positioning accuracy, are unable to reject disturbances in terms of process forces and lack reliable programming and simulation tools to ensure right first time machining, once production commences. These three critical limitations currently prevent the use of robots in typical machining applications. The COMET project is co-funded by the European Commission as part of the European Economic Recovery Plan (EERP) adopted in 2008. The EERP proposes the launch of Public-Private Partnerships (PPP) in three sectors, one of them being Factories of
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