Vehicle Manufacturers Research Articles

Vehicle Sideslip Angle estimation under critical road conditions via nonlinear Kalman filter-based state-dependent Interacting Multiple Model approach

The knowledge of Vehicle Sideslip Angle (VSA) can play an essential role in active safety vehicle control systems. However, due to the high costs of sensing instruments, this information is difficult to be directly measured onboard of series production vehicles, restricting de facto its application in practice. It follows that there is a need for online VSA estimation methods only based on available measurements from low-cost sensors. From this perspective, this work proposes a strategy based on Interacting Multiple Model (IMM) filters, which does not require tyre–road friction coefficient knowledge. By integrating the available onboard sensor data, the IMM estimates relevant information in different driving conditions leveraging a 2-Degrees Of Freedom (DOF) single-track vehicle model embedding a Dugoff tyre representation. Two alternative IMM algorithms based on the Extended (EKF) and Unscented Kalman filter (UKF) are developed. Moreover, while usually the transition probabilities among models in classical IMMs are fixed and set on prior information and/or dedicated analysis, here these conservative hypotheses are relaxed introducing a state-dependent Markov transition matrix based on a novel model switching algorithm. The effectiveness of the new proposed methods is evaluated on extensive non-trivial simulation scenarios through a Monte Carlo analysis exploiting an accurate 15-DOF vehicle model via a purposely designed high-fidelity co-simulation platform embedding the dSPACE software Automotive Simulation Model (ASM). Results provide a meaningful comparative performance analysis between the IMMEKF and IMMUKF solutions, as well as with respect to traditional IMM based on constant probabilities transition matrix, blue in both the EKF and UKF configuration. Finally, the developed IMM-based estimation strategy is tested in two realistic driving scenarios to assess the VSA estimation accuracy in case of abrupt changes in road surface conditions.

A novel UEBASC‐qZSI‐based BLDC motor drive with modified DTC for EV application

SummaryAt present taking into account the situation of the environment and the growing demand of fossil fuels, electric vehicles (EVs) are a highly promising option for the transportation system. Many manufacturers of electric vehicles employ BLDC motors as the vehicle's driving component. In contrast to the many advantages that BLDC motors offer, one of the major drawbacks of employing these motors is the production of relatively high distortion in electromagnetic torque that is created by commutation. This distortion in torque has an effect on the vehicle's performance. In this proposed work a BLDC motor is powered by a cutting‐edge, highly gained q‐ZSI Ultra‐Extended Boost Active Switch Controlled Based Quasi Z‐source Inverter, or UEBASC‐qZSI. In the aforementioned drive, the torque distortion is minimized with the use of a modified direct torque control approach. With the aid of this UEBASC‐qZSI, the efficiency of EVs can be improved, and the overall safety of the driving cycle is also increased. Any vehicle's efficiency can be enhanced with the help of this UEBASC‐qZSI, and the overall safety of the overall system can also be improved. To validate the efficacy of the system, a Simulink model is developed in the MATLAB platform. Also, a hardware prototype model is developed for experimental authentication. The modeling and investigational findings demonstrate that the proposed system has significantly reduced the torque ripple while obtaining the necessary input dc bus voltage.

Experimental research on vehicles equipped with a GMP Hybrid for the new Euro 7 emissions standard

With the increase the number of vehicles on European roads, the road transport has become the biggest source of air pollution in the cities of the old continent. According to European Commission estimates in 2018, more than 39% of NOx (nitrogen oxides) emissions and 10% of PM2.5 and PM10 emissions (mechanical particles with diameters of 2.5 and 10 micrometers) were attributed to road transport. It is known that, in order to limit to some extent, the uncontrolled increase in harmful emissions from road vehicles, the European Commission has gradually introduced new pollution standards to be met by manufacturers of new vehicles. In the second half of 2022, the Commission presented a new proposal to reduce pollutant emissions from new vehicles sold in the European Union (EU), defining the new Euro 7 pollution standards. Compared to Euro 6 by 2035, according to European Commission estimates, these new Euro 7 standards, together with a progressive increase in the number of electric vehicles sold, aim to reduce pollutant emissions from private vehicles and vans by around 35% for NOx emissions and around 13% for particulate emissions. Therefore, both the Euro 7 and CO2 emissions standard (CAFE) for vehicles have been designed to improve air quality in cities and reduce greenhouse gas emissions, including by increasing the use of electric vehicles. Starting from this hypothesis, the first part of the paper presents the experimental model developed in the AMESim simulation platform of a mid-size vehicle equipped with a hybrid GMP, tested on a roller bench, which simulates pollutant emissions in this new Euro 7 standard. In the second part of the paper, the simulation results and possible causes influencing hybrid GMP behavior leading to the evolution of pollutant emissions are analyzed. Finally, the paper formulates conclusions on the evolution of pollutant emissions.

Study of on-board equipment of modern uavs

This paper analyzes the development and production of modern unmanned aerial vehicles (UAVs). It is noted that they have the following main systems: glider; propulsion system; power supply system; management system; navigation system; telemetry system; radio communication system. All UAV systems are interconnected and work as one complex mechanism. Depending on the list of combat tasks to be solved, the following devices can be additionally installed on board the UAV: optical-electronic, thermal imaging, radar, radiotechnical, radiation, chemical, bacteriological and other types of reconnaissance systems with small intelligence storage systems; means of setting active radio-electronic jammers; means of aiming and adjusting guided weapons; various means of defeat; means of control and communication with the ground control point; responsible for the state identification system; autonomous flight and automatic landing devices. The work reveals the features of the UAV engine design, it is noted that 4, 6 or more engines are installed on modern helicopter-type UAVs, so-called "multicopters", "quadracopters", "drones". In this work, it is noted that the UAV navigation equipment can have various level of complexity and use several signals coming from sensors of different physical origins to calculate its location. The features of the UAV radio communication system are revealed, which is a set of various lines through which intelligence information of various levels of importance and protection is transmitted. All communication links can use different frequency bands and different relay modes, use different signal-code designs, specially adapted to the importance of the intelligence information being transmitted. It was noted that in the absence of a control command, the UAV goes into autonomous flight mode.

Dynamic game evolution complexity of new energy and fuel vehicle manufacturers under carbon cap‐and‐trade policy

AbstractConsidering customers' preferences for low‐carbon products, the paper delves into the short‐run and long‐run repetitive game involving three oligopolistic manufacturers engaged in the production of new energy vehicles (hybrid electric vehicles [HEV] and battery electric vehicles [BEV]) and conventional fuel vehicles (FV) within the framework of a carbon cap‐and‐trade policy (CaT). In the short‐run game model, this study explores the optimal decision of oligarchic manufacturers and analyzes the efficiency of the supply chain in the context of cooperation and non‐cooperation. In the long‐run repetitive scenario, the article examines the optimal decision of the manufacturer, assuming rational economic behavior aimed at maximizing individual profits within a non‐cooperation game strategy. Finally, the paper investigates the elements that influence the efficiency of the supply chain. The results reveal that (1) fuel vehicles possess greater flexibility in adjusting parameters compared to the other vehicle types; a judicious increase in manufacturers' price adjustment parameters in the stability domain is beneficial to their respective profits and enhances the overall supply chain profitability. (2) Maintaining customers' preference for low‐carbon products within a reasonable range is crucial for the mutual benefit of all manufacturers. (3) The government needs to allocate more carbon emission limits to fuel vehicle manufacturers in order to improve supply chain efficiency.

Penerapan Algoritma Artificial Neural Network dan Economic Order Quantity dalam Memprediksi Persediaan Pengendalian BBM

Motor vehicle production in Indonesia increases every year along with increasing demand for fuel as a raw material. Generally, gas stations carry out the process of ordering fuel from Dempo on an irregular basis, the frequency of orders does not have a certain time, orders depend on sales transactions and the amount of fuel inventory available depends on the fuel in storage. Regarding prediction and control of fuel supplies, the risk at gas stations is that the volume of fuel received is different from that ordered. It is suspected that tank trucks carrying fuel during delivery from the depot to gas stations tend to experience evaporation in the tank (loses), so that the fuel quantity decreases. Requests for fuel filling are only based on monitoring without any special calculations resulting in stock being maintained and not covering consumer demand. This research is to analyze the Artificial Neural Network algorithm in predicting fuel, and determine inventory control using Economic Order Quantity. The research was conducted using data from November 2020 - October 2023. The data was processed using the ANN algorithm using Google Colab, and continued with EOQ using Microsoft Excel. The ANN parameters are 1 hidden layer with 100 units, Adam optimizer, learning rate 0.001, batch size 8 and epoch 200. Pertalite ANN test results are MSE 248852593.81 and MAE 12749.45, while Pertamax Turbo MSE 803842.94 and MAE 672, 74 provides predictions for November and December of 11,1436.82 L and 11,1960.83 L and Pertamax Turbo of 3,782.46 L and 3,660.70 L. Furthermore, in 2023 the fuel EOQ of Pertalite and Pertamax Turbo will be 8,445 L and 5,261 L, Safety Stock 3,516 L and 1,064 L, Maximum Inventory 6,042 L and 5,153 L, Re order point 2,403 L and 108 L, Order frequency 149 times and 6 times with Total Inventory Cost Rp. 178,830,302 and Rp. 7,700,459.

Development and Analysis of an On-Road Torque Measurement Device for Trucks

BackgroundRolling resistance and aerodynamic losses cause a significant part of a truck’s energy consumption. Therefore there is an interest from both vehicle manufacturers and regulators to measure these losses to understand, quantify and reduce the energy consumption of vehicles. On-road measurements are particularly interesting because it enables testing in various ambient conditions and road surfaces with vehicles in service.ObjectiveCommon driving loss measurement devices require unique instrumented measurement wheels, which hinders effective measurements of multiple tyre sets or measurements of vehicles in service. For this purpose, the objective is to develop a novel load-sensing device for measuring braking or driving torque.MethodsThe strength of the measurement device is calculated using finite element methods, and the output signal is simulated using virtual strain gauge simulations. In addition to the signal simulation, the device is calibrated using a torsional test rig.ResultsThe simulation results confirm that the device fulfils the strength requirements and is able to resolve low torque levels. The output signal is simulated for the novel cascaded multi-Wheatstone bridge using the strains extracted from the finite element analysis. The simulations and measurements show that the measurement signal is linear and not sensitive to other load directions. The device is tested on a truck, and the effort of mounting the device is comparable to a regular tyre change.ConclusionsA novel driving loss measurement device design is presented with an innovative positioning of strain gauges decoupling the parasitic loads from the driving loss measurements. The design allows on-road testing using conventional wheels without requiring special measurement wheels or instrumentation of drive shafts, enabling more affordable and accurate measurements.

Frontiers in Operations: Battery as a Service: Flexible Electric Vehicle Battery Leasing

Problem definition: The electric vehicle (EV) manufacturer NIO adopts a swappable-battery design and a battery-leasing business model known as battery as a service (BaaS). It recently introduced flexible battery leasing, which allows customers to temporarily up-/downgrade their primary leased batteries based on the needs for range. We investigate whether this business model innovation is viable, namely whether introducing flexible battery leasing in BaaS could benefit the manufacturer, the customers, and the environment compared with simple battery leasing. Methodology/results: Adopting a game-theoretical model, we find that introducing flexible battery leasing in BaaS can simultaneously improve the manufacturer profit as well as reduce the total customer cost and the total battery capacity. Such win-win-win outcomes generally occur for large high-capacity battery ranges and moderate high-capacity battery costs—both consistent with the ongoing trend in the EV industry and a model-calibration exercise. We further show that this key finding is robust for correlated regular and peak needs for range and when launching BaaS with flexible battery leasing and that if the manufacturer was to choose a high-capacity battery range for flexible battery leasing, it would choose one such that battery reallocation alone can meet all battery up-/downgrade demand without acquiring additional batteries. Managerial implications: Our findings confirm that flexible battery leasing can be a viable BaaS business model innovation and offer insights into when this may be the case. This insight strengthens the strategic support for EV manufacturers’ potential adoption of the swappable-battery design and the BaaS model, and it may inform their operating policies to implement flexible battery leasing. History: This paper has been accepted in the Manufacturing & Service Operations Management Frontiers in Operations Initiative. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0587 .

An Estimate of the NOX Emissions of Euro 6 Diesel Passenger Cars with Manipulated Emission Control Systems

The motivation for conducting this research stems from the increasingly applied manipulations of emission control systems (ECSs), especially those in diesel passenger cars (PCs). The study aimed to investigate the influence of manipulations of exhaust gas recirculation (EGR) valves and a diesel exhaust fluid (DEF)-dosing system on the nitrogen oxide (NOX) emissions of a Euro 6 diesel vehicle and, through the quantification of vehicles with manipulated ECSs, estimate the emissions of Euro 6 diesel PCs. Portable emissions measurement system (PEMS) measurements were performed on a Euro 6 diesel vehicle at a constant speed and on real driving emission (RDE) routes. The speed-dependent functions of the NOX hot emission factor (EF) were calculated for seven different scenarios. The results showed that the NOX EFs for the worst-case scenarios were more than two orders of magnitude higher than those where all ECSs were active. Applying the calculated EFs and the survey answers on the percentage of manipulated PCs to the Croatian Euro 6 diesel PC fleet, the results showed that the emission levels were up to 46.3% higher than the emissions calculated by the official computer program COPERT v5.6.5, with a tendency towards significantly higher values. The main conclusion is that vehicle manufacturers, policymakers, and the general public need to be informed about the enormous damage that in-use vehicles with manipulated ECSs cause to the environment and human health, in order to prevent such actions.

Dual Redox Mediators Assisted Hierarchically Porous Hollow Carbon Shell Cathode for Enhanced Performance Li‐O2 Battery

AbstractRechargeable lithium‐oxygen (Li‐O2) batteries with high theoretical energy density are regarded as a promising candidate for the booming electric vehicle manufacturing industry, whereas their commercial application is hindered due to poor cyclic stability caused by the sluggish kinetics and inevitable cathode passivation. Herein, a synergistic working mechanism of Li‐O2 battery is initiated by implementing well‐designed hollow carbon shells with hierarchically porous hollow structure (HCS) assisted by dual redox mediators (RMs) simultaneously, so as to systemically address issues of diminished discharge capacity and reaction kinetics. The hierarchically porous structure of HCS constructs more space to accommodate Li2O2, increases the accessibility of active sites, and enhances discharge capacity. More importantly, the dual RMs regulate the growth mechanism of Li2O2 in surface‐mediated mode, resulting in an easily decomposed film‐like Li2O2 with higher electron transport capacity and improving the reaction kinetics. As a result of the synergistic effort, an HCS‐based Li‐O2 battery with dual RMs manifests a total discharge capacity of 24580 mA h g−1 and a prolonged cycle life of 2500 h at the current density of 100 mA g−1. This design philosophy will open up a new way to optimize and upgrade the cathode materials of Li‐O2 batteries.

Can-train-and-test: A curated CAN dataset for automotive intrusion detection

When it comes to in-vehicle networks (IVNs), the controller area network (CAN) bus dominates the market; automobiles manufactured and sold worldwide depend on the CAN bus for safety-critical communications between various components of the vehicle (e.g., the engine, the transmission, the steering column). Unfortunately, the CAN bus is inherently insecure; in fact, it completely lacks controls such as authentication, authorization, and confidentiality (i.e., encryption). Therefore, researchers have travailed to develop automotive security enhancements. The automotive intrusion detection system (IDS) is especially popular in the literature—due to its relatively low cost in terms of money, resource utilization, and implementation effort. That said, developing and evaluating an automotive IDS is often challenging; if researchers do not have access to a test vehicle, then they are forced to depend on publicly available CAN data—which is not without limitations. Lack of access to adequate CAN data, then, becomes a barrier to entry into automotive security research.We seek to lower that barrier to entry by introducing a new CAN dataset to facilitate the development and evaluation of automotive IDSs. Our datasets—dubbed can-dataset, can-log, can-csv, can-ml, and can-train-and-test—provide CAN data from four different vehicles produced by two different manufacturers. The attack captures for each vehicle model are equivalent, enabling researchers to assess the ability of a given IDS to generalize to different vehicle models and even different vehicle manufacturers. Our datasets contain replayable .log files as well as labeled and unlabeled .csv files, thereby meeting a variety of development and evaluation needs. In particular, the can-train-and-test dataset offers nine unique attacks, ranging from denial of service (DoS) to gear spoofing to standstill; as such, researchers can select a subset of the attacks for training and save the remainder for testing in order to assess a given IDS against unseen attacks. Many of our attacks, particularly the spoofing-related attacks, were conducted during live, on-the-road experiments with real vehicles. These attacks have known physical impacts. As a benchmark, we pit a number of machine learning IDSs against our dataset and analyze the results. We present our datasets—especially can-train-and-test—as a contribution to the existing catalogue of open-access datasets in hopes of filling in the gaps left by those datasets.

Technical analysis and performance evaluation of retrofitted electric Auto Rickshaws (E-TAR) in rural India

India needs to electrify rickshaws because of the emissions produced by modern cars running on fossil fuels like gasoline and diesel. There are incentives, discounts, and exemptions available for the use of e-auto rickshaws. The production of electric vehicles has also been given a target by the Indian government. The Indian government has taken a number of steps to increase the availability of charging stations and a steady supply of electric cars (EVs). Even after taking all of these measures, there has been little adoption. For Indian auto drivers, the capital cost of purchasing an e-auto is expensive. To attain ideal performance, it is important to modify the present generation of traditional auto rickshaws using low-cost retrofitting. Retro-kit is created and evaluated for performance in this study by changing parameters.

How social media expedites the crisis spillover effect: A case study of Tesla's recall event

Technologies such as intelligent and fully automatic driving are currently developing rapidly. However, product recalls by electric vehicle manufacturers occur frequently because of immature technology. As a crisis factor, product recalls of the focal company pose a risk of contagion to other players. Through a two-period time series analysis, the current study observes that online public opinion regarding Tesla exerts an indirect spillover over abnormal returns on non-focal companies (i.e., BYD, NIO, LI) from two aspects—social media buzz and public sentiment. Moreover, abnormal returns on Tesla directly spill over into abnormal returns on NIO and LI. The low brand equity proximity plays a role in the direct spillover effect. Besides, the time lag is two days in the direct and indirect spillover process. Under the guidance of Situational Crisis Communication Theory (SCCT), we classify spillover crises as victim clusters of crisis types and put forth implications and suggestions in practice based on our findings.

Modular Autonomous Vehicles’ Application in Public Transport Networks: Conceptual Analysis on Airport Connection

Increased efficiency and optimized operation of transport networks represent two of the main topics of interest when discussing modern road vehicle solutions. Taking steps towards more sustainable options, manufacturers of road vehicles are looking into advanced technologies that allow vehicles to run more efficiently and take advantage of all the available data on the road. When looking at public transportation applications, trends point in the direction of using varied types of vehicles that can carry people around. The intermodality of these types of vehicles represents the most optimized way of traveling, combining the fast and secure characteristics of airplanes and trains with the flexibility of last-mile options, such as taxis, buses, or trams. This paper discusses the aspects of implementing a modular autonomous vehicle (MAV) solution for the last-mile part of travel routes, connecting key points of a city, such as an airport or a train station, to other key locations in the city, such as the city center, important facilities, or marginal neighborhoods.

Investigation on the Effect of Blank Holder Force and Initial Blank Size on the Thinning Problem of the Fuel Tank Part Made from Aluminum Alloy Sheet 5754-O under Deep Drawing Process

Deep drawing process is a common sheet metal forming technique in motor vehicle manufacturing. There are three primary defects that could be occur in deep-drawn parts: tearing, wrinkling, and thinning. When the thinning is difficulty detected by visual inspection. As a result, this study aims to address the thinning issue in a fuel tank part made from an aluminum alloy sheet AA5754-O 1.5 mm thick under cold working deep drawing process, while the manufacturer's desired upper limit for thinning is 20%. Two influential parameters viz. blank holder force and initial size of blank, were investigated and optimized by using Finite Element Analysis (FEA) through PAM-STAMP simulation software with the validated material model was based on Hill’s 1948 anisotropic yield criterion with Swift hardening law. The mechanical parameters in the mentioned model were derived from the results of uniaxial tensile tests. In conclusion, both the hydraulic cushion's blank holder pressure and the initial size of the blank were found to influence the thinning of the part, either individually or in combination. Despite optimizing both parameters, they were unable to consistently achieve the desired limit.

Effect of gasoline-ethanol blends on the performance of a four stroke engine using Ricardo Wave software

Purpose The purpose of this study is to assess the performance of fuel blends containing ethanol and gasoline in spark ignition engines. The aim is to explore alternative fuels that can enhance performance while minimizing or eliminating adverse environmental impacts, particularly in the context of limited fossil fuel availability and the need for sustainable alternatives. Design/methodology/approach The authors used the Ricardo Wave software to evaluate the performance of fuel blends with varying ethanol content (represented as E0, E10, E25, E40, E55, E70, E85 and E100) in comparison to gasoline. The assessment involved different composition percentages and was conducted at various engine speeds (1,500, 3,000, 4,500 and 6,000 rpm). This methodology aims to provide a comprehensive understanding of how different ethanol-gasoline blends perform under different conditions. Findings The study found that, across all fuel blends, the highest brake power (BP) and the highest brake-specific fuel consumption (BSFC) were observed at 6,000 rpm. Additionally, it was noted that the presence of ethanol in gasoline fuel blends has the potential to increase both the BP and BSFC. These findings suggest that ethanol can positively impact the performance of spark-ignition engines, highlighting its potential as an alternative fuel. Originality/value This research contributes to the ongoing efforts in the automotive industry to find sustainable alternative fuels. The use of Ricardo Wave software for performance assessment and the comprehensive exploration of various ethanol-gasoline blends at different engine speeds add to the originality of the study. The emphasis on the potential of ethanol to enhance engine performance provides valuable insights for motor vehicle manufacturers and researchers working on alternative fuel solutions.

Effects of different design and lightweight material on energy distribution and collision characteristics for hot-formed B-pillar using finite element simulation

In line with international environmental policies and efforts to reduce carbon emissions, the number of electric vehicles also shows a sharp increase. This increase is aimed at reducing energy use, vehicle lightening, and increasing passenger safety by leading vehicle manufacturers to use new generation materials. However, the use of newly developed materials in the automotive industry takes a long time, and the developments in the field of materials and vehicle technologies are progressing at different speeds. In this study; the B-pillar part of a B-segment car was analyzed with HPF2000 material instead of the current HPF1500 material using the finite element method. The designs prepared as two different options were simulated with Ls-Dyna according to EuroNCAP side impact test standards. As a result of the simulations, the effects of different design and material variables on energy absorption, collision characteristics, and lightness were examined. It was seen that the energy absorbed by the part increased by 2.9% thanks to the new material and design. Specific energy absorption, another feature indicating the collision characteristic, increased by 11.81%. The total weight of the part decreased by 9.7% with using new generation material. In summary; With the use of new generation high-strength hot-formed steels in vehicle parts, besides the vehicle’s lightness, the mechanical properties have improved the collision characteristics and vehicle safety has also increased.

Light Electric Vehicle Performance with Digital Twin Technology: A Comparison of Motor Types

Digital twin (DT) is proposed as a solution to reduce financial and time losses for vehicle manufacturers by streamlining the expensive and time-consuming processes of designing and implementing electric vehicle types and road assessments. The use of digital twins to monitor, evaluate, and optimize vehicle performance based on real-time road data is increasingly crucial in the DT concept. In this study, the digital twin of the CERYAN brand vehicle model has been employed to compare the performance of different motor types (PMSM, PMSM Brushless, BLDC/PMSM Brushless, and BLDC) in terms of energy consumption and acceleration at various inclination angles, utilizing real-time road data. According to the World Motorcycle Test Cycle (WMTC) standards, the motor type with the best performance parameters was determined as a PMSM brushless motor (5 kW). The main superior aspects of the proposed motor type are to achieve a 25% higher range than the BLDC Motor, 30% better grade ascending capability than the PMSM Motor, and 26% lower energy consumption than the PMSM brushless motor (6 kW).

Design Process and Advanced Manufacturing of an Aquatic Surface Vehicle Hull for the Integration of a Hydrogen Power Plant Propulsion System

This article presents the design and manufacturing of a hydrogen-powered unmanned aquatic surface vehicle (USV) hull. The design process comprised three stages: (1) defining the requirements for a preliminary geometry, (2) verifying the hydrodynamic hull performance using computational fluid dynamics (CFD) simulations, and (3) experimentally validating the hydrodynamic hull performance and CFD analysis results through experimental fluid dynamics in a calm water towing tank. The manufacturing process utilized additive manufacturing technologies, such as fused granular fabrication and selective laser sintering, to produce the hull and other components, including the propeller and the rudder; thermoplastic materials with carbon fiber reinforcement were employed. The experimental results demonstrate that the optimized trimaran hull exhibited low hydrodynamic resistance (7.5 N), high stability, and a smooth flow around the hull (up to 2 m/s). The design and manufacturing of the USV hull met expectations from both hydrodynamic and structural perspectives, and future work was outlined to integrate a power plant, navigation system, and scientific equipment.

Design And Simulation Of 10 kW BLDC Motor Speed Control For Electric Vehicles Using FOC Based On Fuzzy Logic Control

The use of electric vehicles in the current era has begun to spread evenly. Apart from the issue of air pollution produced by ICE vehicles, the ease and practicality of using electric vehicles is the reason why the public is starting to become interested in electric vehicles. Electric vehicle manufacturers are currently choosing BLDC motors for their production vehicles because they are considered suitable for applications that require high power and torque output. However, BLDC motors require more complicated control techniques than other DC motors. The commonly used BLDC motor speed control methods are trapezoidal scalar control and field oriented control. FOC is a type of BLDC motor control with a vector control method which has advantages in terms of efficiency compared to scalar control methods. Many studies on implementing FOC as speed control for BLDC motors, but the research that has been carried out still uses PI control as a basis, where it is known that PI control has shortcomings in the form of complexity in its design. Fuzzy Logic Control is known to be easy to design and reliable in control, so this paper will show the performance of Fuzzy-PI based FOC control as speed control for 10kW BLDC motor in simulation using Simulink program. The simulation results of proposed Fuzzy-PI based FOC method have better response than PI based FOC in terms of starting response with 6.43 times faster rise time, 2.45 times faster settling time, 96.31% lower overshoot value and reliability in overcoming disturbances up to 78.05% lower overshoot value and 2.33 times faster recovery time.