SLIDING MODE BASED PREDICTIVE CONTROLLER OF A SPHEROIDAL UNDERWATER VEHICLE

This paper focuses on hydrodynamic modeling and control of spheroidal underwater vehicle. The vehicle considered in this paper is appendage free and unstable. Water jet propulsion system is used in this vehicle. The dynamics of the vehicle is highly unstable due to munk moment. The spheroidal shape underwater robot is used in nuclear reactor inspection, port security inspection, defence and ocean surveillance where external appendages are not required. A new and innovative control technique, Sliding mode based model predictive control is introduced in this paper. Sliding mode control technique is used to stabilize the vehicle and once the vehicle model is stabilized it is easy to apply Model Predictive Control (MPC). Model Predictive control technique is used to control the heading of spheroidal underwater vehicle. Simulation results show that the Sliding mode based predictive control performance is better than simple PD control and state feedback controller.

Development of a Hybrid Electric Vehicle Simulation Tool with a Rule-Based Topology

The performance of hybrid electric vehicles (HEVs) greatly depends on the various sub-system components and their architecture, and designers need comprehensive reviews of HEVs before vehicle investigation and manufacturing. Simulations facilitate development of virtual prototypes that make it possible to rapidly see the effects of design modifications, avoiding the need to manufacture multiple expensive physical prototypes. To achieve the required levels of emissions and hardware costs, designers must use control strategies and tools such as computational modeling and optimization. However, most hybrid simulation tools do not share their principles and control logic algorithms in the open literature. With this motivation, the author developed a hybrid simulation tool with a rule-based topology. The major advantage of this tool is enhanced flexibility to choose different control and energy management strategies, enabling the user to explore a wide range of hybrid topologies. The tool provides the user with the ability to modify any sub-system according to one’s own requirements. In addition, the author introduces a simple logic control for a rule-base strategy as an example to show the flexibility of the tool in allowing the adaptation of any logic algorithm by the user. The results match the experimental data quite well. Details regarding modeling principle and control logic are provided for the user’s benefit.

The Role of Smart Technologies to Improve the Utilization of Wood Uses in Engineering Applications: A Review

Nowadays, smart technology plays an important role in engineering applications to improve the quality of life. Thus, the development of natural materials and the use of nanotechnology, will give wood new properties to maximize its benefit. It is clear that there is a great challenge to prove the strength and durability of wood acquiring new features to reach innovative use that can influence the current path in many engineering applications. Therefore, this paper summarizes a review of the possibility of using nano- and smart-technologies to make the most of the natural and acquired potential for adding new features and physical properties of wood to improve its efficiency in architectural and mechanical applications. Moreover, experiments have shown that the use of certain types of wood in many applications such as the manufacture of 3D vehicle simulation models to study dynamic behaviors as well as in the manufacture of mechanical measurement systems to improve accuracy. In conclusion, new directions under development in this field are proposed to provide solutions to important issues in the future of measurement and quality control systems that need scientific treatment.--

Overview of Intelligent Vehicle Infrastructure Cooperative Simulation Technology for IoV and Automatic Driving

This paper reviews the development of vehicle road collaborative simulation in the new era, and summarizes the simulation characteristics of two core technologies in the field of transportation after entering the era of Intelligent Networking: Internet of Vehicles technology and automatic driving technology. This paper analyzes and compares the mainstream Internet of Vehicles (IoV) simulation and automatic driving simulation platforms on the market, deeply analyzes the model-based IoV simulation, and explores a new mode of IoV simulation in the era of big data. According to the latest classification standard of automatic driving in 2020, we summarize the simulation process of automatic driving. Finally, we offer suggestions on the development directions of intelligent network-connected vehicle simulation.

Design and Validation of Thermal Insulation for Deep-sea Fluid Sampler of Jiaolong Human Occupied Vehicle

In this paper, a thermal insulation structure with silica aerogel felt as filler material was designed for the requirements of deep-sea fluid thermal insulation sampling technology for Jiaolong human occupied vehicle. Simulation analysis of thermal insulation performance was carried out and an experimental prototype was developed for the thermal insulation structure. Experimental study on thermal insulation performance was conducted with the variation characteristics of the operation environment for Jiaolong human occupied vehicle being taken into account. Results show that the silica aerogel felt with a thickness of 30 mm filled in the radial space between the inner and outer cylinders can achieve the expected thermal insulation effect during the diving-sampling-transferring process, with maximum temperature rise of 8.5 °C, and can meet the requirements of deep-sea fluid thermal insulation sampling technology.

Human-like Interactive Behavior Generation for Autonomous Vehicles: A Bayesian Game-theoretic Approach with Turing Test

Interacting with surrounding road users is a key feature of vehicles and is critical for intelligence testing of autonomous vehicles. The Existing interaction modalities in autonomous vehicle simulation and testing are not sufficiently smart and can hardly reflect human-like behaviors in real world driving scenarios. To further improve the technology, in this work we present a novel hierarchical game-theoretical framework to represent naturalistic multi-modal interactions among road users in simulation and testing, which is then validated by the Turing test. Given that human drivers have no access to the complete information of the surrounding road users, the Bayesian game theory is utilized to model the decision-making process. Then, a probing behavior is generated by the proposed game theoretic model, and is further applied to control the vehicle via Markov chain. To validate the feasibility and effectiveness, the proposed method is tested through a series of experiments and compared with existing approaches. In addition, Turing tests are conducted to quantify the human-likeness of the proposed algorithm. The experiment results show that the proposed Bayesian game theoretic framework can effectively generate representative scenes of human-like decision-making during autonomous vehicle interactions, demonstrating its feasibility and effectiveness. Corresponding author(s) Email: [email protected]

IMPORTANCE OF 3D VEHICLE HEAT EXCHANGER MODELING

The work demonstrates, via a comprehensive study, the necessity of using a 3D CFD approach for heat exchanger (HTX) modelling within underhood vehicle simulation. The results are presented as the difference between 1D and 3D CFD approaches with a focus on auxiliary fluid (e.g. coolant) temperature prediction as a function of primary fluid (e.g. air) inlet conditions. It has been shown that the 1D approach could significantly underpredict auxiliary fluid inlet temperature due to neglecting the spatial distribution of primary fluid velocity magnitude. The resultant difference in the auxiliary fluid flow HTX inlet temperature is presented and discussed as a function of the Uniformity Index (UI) of the primary fluid flow velocity magnitude. Additionally, the 3D HTX model's importance is demonstrated in an industrial example of full 3D underhood simulation.

Operational features of battery-powered electric vehicles in Russia and methods of assessing a state of health of traction batteries

Electric vehicle manufacturers pay particular attention to climatic conditions in the Russian Federation, seeing that chemical reaction rates usually decrease when the environment temperature drops. The analysis of ambient temperature data in the region where electric vehicles will most likely be used aims to select extreme temperatures for calculating powers of a thermostat control system for traction batteries. An electric vehicle simulation model to calculate the power of the thermostat control system for traction batteries is described. An empirical model to assess a state of health of traction batteries is selected. This simulation model adequately reflects thermal processes in a traction battery and can be used for further research.

Impacts of Extreme Ambient Temperatures and Road Gradient on Energy Consumption and CO2 Emissions of a Euro 6d-Temp Gasoline Vehicle

The EU aims to substantially reduce its greenhouse gas emissions in the following decades and achieve climate neutrality by 2050. Better CO2 estimates, particularly in urban conditions, are necessary for assessing the effectiveness of various regional policy strategies. In this study, we measured the CO2 emissions of a Euro 6d-temp gasoline direct injection (GDI) vehicle with a three-way catalyst (TWC) and a gasoline particulate filter (GPF) at ambient temperatures from −30 °C up to 50 °C with the air-conditioning on. The tests took place both on the road and in the laboratory, over cycles simulating congested urban traffic, dynamic driving, and uphill driving towing a trailer at 85% of the maximum payloads of both the car and the trailer. The CO2 values varied over a wide range depending on the temperature and driving conditions. Vehicle simulation was used to quantify the effect of ambient temperature, vehicle weight and road grade on the CO2 emissions. The results showed that vehicle energy demand was significantly increased under the test conditions. In urban trips, compared to the baseline at 23 °C, the CO2 emissions were 9–20% higher at −10 °C, 30–44% higher at −30 °C, and 37–43% higher at 50 °C. Uphill driving with a trailer had 2–3 times higher CO2 emissions. In motorway trips at 50 °C, CO2 emissions increased by 13–19%. The results of this study can help in better quantification of CO2 and fuel consumption under extreme conditions. Additional analysis on the occurrence of such conditions in real-world operation is advisable.