Precise Flow Control Research Articles

Optofluidic paper-based analytical device for discriminative detection of organic substances via digital color coding

Developing a portable yet affordable method for the discrimination of chemical substances with good sensitivity and selectivity is essential for on-site visual detection of unknown substances. Herein, we propose an optofluidic paper-based analytical device (PAD) that consists of a macromolecule-driven flow (MDF) gate and photonic crystal (PhC) coding units, enabling portable and scalable detection and discrimination of various organic chemical, mimicking the olfactory system. The MDF gate is designed for precise flow control of liquid analytes, which depends on intermolecular interactions between the polymer at the MDF gate and the liquid analytes. Subsequently, the PhC coding unit allows for visualizing the result obtained from the MDF gate and generating differential optical patterns. We fabricate an optofluidic PAD by integrating two coding units into a three-dimensional (3D) microfluidic paper within a 3D-printed cartridge. The optofluidic PADs clearly distinguish 11 organic chemicals with digital readout of pattern recognition from colorimetric signals. We believe that our optofluidic coding strategy mimicking the olfactory system opens up a wide range of potential applications in colorimetric monitoring of chemicals observed in environment.

Turbulent Flow Through Sluice Gate and Weir Using Smoothed Particle Hydrodynamics: Evaluation of Turbulence Models, Boundary Conditions, and 3D Effects

Understanding flow dynamics around hydraulic structures is essential for optimizing water management systems and predicting flow behavior in real-world applications. In this study, we simulate a 3D flow control system featuring a sluice gate and a weir, commonly used in hydraulic engineering. The focus is on accurately incorporating modified dynamic boundary conditions (mDBCs) and viscosity treatment to improve the simulation of complex, turbulent flows. We assess the performance of the Smoothed Particle Hydrodynamics (SPH) method in handling these challenging conditions. Especially when the boundary conditions and applicability to industry are two of the SPH method’s grand challenges. Simulations were conducted on a Graphics Processing Unit (GPU) using the DualSPHysics code. The results were compared to theoretical predictions and experimental data found in the literature. Key hydraulic characteristics, including 3D flow effects, hydraulic jump formation, and turbulent behavior, are examined. The combination of mDBCs with the Laminar plus sub-particle scale turbulence model achieved the correct simulation results. The findings demonstrate agreement between simulations, theoretical predictions, and experimental results. This work provides a reliable framework for analyzing turbulent flows in hydraulic structures and can be used as reference data or a prototype for larger-scale simulations in both research and engineering design, particularly in contexts requiring robust and precise flow control and/or environmental management.

Aptamer selection via versatile microfluidic platforms and their diverse applications.

Aptamers are synthetic oligonucleotides that bind with high affinity and specificity to various targets, making them invaluable for diagnostics, therapeutics, and biosensing. Microfluidic platforms can improve the efficiency and scalability of aptamer selection, especially through advancements in systematic evolution of ligands by exponential enrichment (SELEX) methods. Microfluidic SELEX methods are less time-consuming and labor-intensive and include critical steps like library preparation, binding, partitioning, and amplification. This review examines the contributions of microfluidic technology to SELEX-based aptamer identification, with alternative methods like conditional SELEX, in vivo-like SELEX and Non-SELEX for selecting aptamers and also discusses critical SELEX steps over the past decade. This work also examined the integrated microfluidic systems for SELEX, highlighting innovations such as conditional SELEX and in vivo-like SELEX. These advancements provide potential solutions to existing challenges in aptamer selection using conventional SELEX, especially concerning biological samples. A trend toward non-SELEX methods was also reviewed and discussed, wherein nucleic acid amplification was eliminated to improve aptamer selection. Microfluidic platforms have demonstrated versatility not only in aptamer selection but also in various detection applications; they allow for precise control of liquid flow and have been essential in the advancement of therapeutic aptamers, facilitating accurate screening, enhancing drug delivery systems, and enabling targeted therapeutic interventions. Although advances in microfluidic technology are expected to enhance aptamer-based diagnostics, therapeutics, and biosensing, challenges still persist, especially in up-scaling microfluidic systems for various clinical applications. The advantages and limitations of integrating microfluidic platforms with aptamer development are further addressed, emphasizing areas for future research. We also present a perspective on the future of microfluidic systems and aptamer technologies, highlighting their increasing significance in healthcare and diagnostics.

Plasmid Stability Analysis with Open-Source Droplet Microfluidics.

Plasmids play a vital role in synthetic biology by enabling the introduction and expression of foreign genes in various organisms, thereby facilitating the construction of biological circuits and pathways within and between cell populations. For many applications, maintaining functional plasmids without antibiotic selection is critical. This study introduces an open-hardware-based microfluidic workflow for analyzing plasmid retention by culturing single cells in gel microdroplets and quantifying microcolonies using fluorescence microscopy. This approach allows for the parallel analysis of numerous droplets and microcolonies, providing greater statistical power compared to traditional plate counting and enabling the integration of the assay into other droplet microfluidic workflows. By using plasmids expressing fluorescent proteins alongside a non-specific fluorescent DNA stain, single colonies can be identified and differentiated based on plasmid loss or fluorescent marker expression. Notably, this advanced workflow, implemented with open-source hardware, offers precise flow control and temperature management of both the sample and the microfluidic chip. These features enhance the workflow's ease of use, robustness, and accessibility. While the study focuses on Escherichia coli as the experimental model, the method's true potential lies in its versatility. It can be adapted for various studies requiring fluorescence signal quantification from plasmids or stains, as well as for other applications. The adoption of open-source hardware broadens the potential for conducting high-throughput bioanalyses using accessible technology in diverse research settings.

New Lyapunov backstepping control of the mechanical power generated by an induction motor

This paper presents a new Lyapunov backstepping control law (LBC) that makes it possible to control the mechanical power generated by an induction motor (IM), while guaranteeing its robustness and stability. This induction motor is supplied by the stator variables via two converters. One, a mains converter (two-level rectifier), facilitates the control of the direct courant (DC) bus and improves the mains power factor; the other, a motor converter (two-level inverter), enables precise control and optimisation of the energy flow during motor operation. In the first part, we presented the modelling of our motor and its converters. In the second part, we presented the control structure proposed to control and optimise the mechanical energy generated by our motor (speed, torque) to achieve optimum efficiency and transfer quality. The results of the numerical simulations demonstrate the effectiveness of the new Lyapunov control system in achieving these objectives, i.e. mechanical speed outside its references and electromagnetic torque below the nominal torque.

Biaxial Thermo–Mechanical Response of ABS Sheet Above Tg Using DIC–Based Bubble Inflation Technique

ABSTRACTIn this study, we examine the biaxial, large, and rapid deformation characteristics of heavy‐gauge ABS sheets within the temperature range of 120°C to 160°C, relevant to the industrial forming process. A custom‐built bubble inflation apparatus with a 300 mm diameter was designed for this purpose. Temperature uniformity across the sheet was verified using a thermal camera, while the temperature profile through the material's thickness was monitored during the heating using thermocouples near the top and bottom surfaces of the sheet. The bubble inflation test, combined with displacement, strain fields, and deformation rates at different locations, enables detailed characterization of the bubble's shape under large deformation. To address early‐stage geometric instabilities due to sagging from thermal expansion, airflow was regulated with a precise flow control valve before inflation, while 3D‐DIC monitored the real‐time displacements to correct for sag deformation. The inflation pressure profile was recorded and synchronized with 3D‐DIC strain evolution data for each test, allowing for analysis of the characteristic stress–strain curve at the pole. By evaluating the material's equi‐biaxial properties at the pole and biaxial strain measurements away from the pole, the collected data provides a strong basis for future calibration of constitutive material models through an inverse approach, enabling accurate integration into process simulations.

EMHD flow and heat transport in cross ternary nanofluid with gyrotactic microorganisms: A case study on thermophoretic particle deposition

The study of ternary nanofluids has gained significant interest in engineering and biomedical applications due to their enhanced thermal conductivity and heat transfer properties. This research specifically focuses on electromagnetic hydrodynamic (EMHD) flow and heat transport in cross-flow ternary nanofluids containing gyrotactic microorganisms, where thermophoretic particle deposition plays a key role. Efficient thermal management and targeted particle deposition are crucial in advanced applications, including solar collectors and biomedical devices. This research presents a comprehensive investigation into the Marangoni convective flow of kerosene oil containing ternary nanoparticles Gra,MgO,andSiO2 over a sheet with significant impact of thermal conductivity varies linearly with temperature. Also, the work utilized the Cross model to capture the shear-thinning features of TNFs, describing their non-Newtonian performance. System of PDEs are achieved and reduced to ODEs using appropriate variables. The spectral collocation method based on Appell-Changhee polynomials was utilized to solve ODEs. The results show that the thermal distribution improves for growing values of exponential heat source and thermal radiation parameter. An increase in the nanoparticle volume fraction parameter reduces the velocity distribution, while the temperature distribution displays an opposite effect. These findings support applications in bioengineering and medical technologies, where precise control of flow and thermal properties is essential.

(Keynote) Soft Wet Iontronic Devices with Affinity to Biosystems

A super-aging society, frequent natural disasters, and coronavirus pandemics are accelerating the transition to a highly efficient DX society. There is also an urgent need to build a DX medical system with online integrated management of self-care (diagnosis and treatment performed by each individual) and self-medication. One of the technological cornerstones of such self-medicine lies in the innovation in "bioaffinity" of wearable and implantable devices that connect between medical systems and living body.Over the past decades, device engineering has pursued bioaffinity through the process of miniaturization and slimming, and recently there is a growing trend to incorporate soft and wet materials with a similar softness to biological tissues in device applications. Furthermore, in addition to these progress in "material affinity", it becomes imperative to drive forward the development of ion-driven molecular delivery and stimulation systems with "affinity to biosystems" to realize truly biocompatible self-care devices.So far, we have studied the materials and technologies for the “Electron ↔ Ion ↔ Molecule ↔ Flow” energy/information multi-conversion, and developed the following iontronic systems to generate ion-flow (1, 2) and drive molecular transports (3, 4).(1) Electron/Ion conversion electrode: Ultra-high capacity electrode materials generate ion current "without electrolysis", ensuring secure and precise stimulation, even in close proximity to living tissues.(2) Molecular/Ion conversion electrode: Converting molecular information/energy into ion current using enzymes as electrocatalysts, enabling devices to be independent of external power sources and linking sensing and stimulation functions.(3) Ion-driven hydrogel pump and switch filter: Precise reversible control of electroosmotic flow electrically (with the ionic flow) using charge-fixed hydrogels. The ion polarity of the electric double layer formed on the micropore wall of the filter is controlled to reversibly switch the direction of electroosmotic flow.(4) Permeable microneedles: Porous microneedle array that provides minimally invasive molecular delivery to pinpoints in biological tissues under control by electroosmotic flow.Utilizing these iontronic systems, we have produced a few self-care devices. Organic intracranial and nerve cuff electrodes composed of hydrogel are is on the verge of being launched [1, 2]. The intracranial electrode has already been employed in epilepsy surgery (the first case of the clinical trial). The prototypes of the bio-powered skin patches [3-5] have shown effects of wound healing and pain relieve. The ion-driven hydrogel pumps and porous microneedles are our important minimally low-invasive interfacing tools [6-9], with which electroosmotic flow can be controlled for drug and vaccine administrations. In this presentation, I will explain these our recent progress in ion-driven self-care devices, and discuss our future plans.

Investigation of Cavitation Phenomena in a “High-Power” Piezohydraulic Pump: A Computational Fluid Dynamics (CFD) Approach

Abstract Piezoelectric pumps, known as piezopumps, are highly versatile devices with applications in various fields due to their precise flow control, compact design, lack of magnetic interference, and low noise. These pumps are classified based on the number of pumping chambers, valve configuration, and driving power source mechanism. In fields requiring consistent flow rates and back pressures, particularly in fluid power applications, piezopumps employing a piezostack actuator as their power driving source are actively researched. This kind of piezopumps, also known as piezohydraulic pumps, operate using a piezostack actuator to drive a piston for fluid delivery, along with reed valves controlling fluid flow at the inlet and outlet of the pump chamber. The high operating frequency range of the piezostack actuator and reed valves, exceeding 1 kHz, allows piezohydraulic pumps to achieve significant flow rates despite the stack’s limited displacement. This enhances their performance without the need for increased size or power input. However, this also increases the risk of cavitation, which could lead to damage, reduced efficiency, and higher noise levels. Therefore, the purpose of this paper is to expand on previous research by using the CFD software Ansys Fluent to further investigate cavitation phenomena in a piezohydraulic pump developed at the University of Bath. In particular, the study focuses on simulating various oil flow scenarios through the pump with a fixed inlet pressure of 20 bar, while varying the opening of the inlet reed valve from the minimum (0.1 mm) to maximum (0.7 mm) value, as well as adjusting the pump chamber pressure.

Evaluation of dental students' learning curve in intraligamentary anesthesia using different syringe systems: A prospective crossover study.

This prospective crossover preclinical trial aimed to evaluate the learning curve of dental students in successfully administering intraligamentary anesthesia (ILA) using three different syringe systems. Dental students performed ILA using three devices in two separate sessions, each targeting mandibular and/or maxillary premolars. The devices included two manual systems (pistol-type and lever-based) and one computer-controlled local anesthetic delivery system (CCLAD). The primary research parameter was the success rate of anesthesia, defined as the percentage of successful ILA administrations confirmed by a negative response to a cold test. Secondary parameters included pain experienced during needle penetration and injection, students' self-reported levels of mental tension and handling of the syringes, and any potential side effects. A total of 110 students performed ILA on 599 teeth during the study period. When comparing the CCLAD system to the manual syringes, the CCLAD system exhibited a significantly higher overall success rate in the first session (92.5% vs. 77.4%; p<0.001), potentially due to its precise control of anesthetic flow and pressure, which likely facilitated more effective anesthetic delivery. However, when examining the individual manual techniques, no significant difference was found between the pistol-type manual and the CCLAD system (p=0.66). All techniques' success rate increased from the first to the second session (80.4% vs. 86.9%; p=0.0357). Additionally, penetration pain demonstrated a significant decrease across all techniques (p<0.01). Notably, students' anxiety levels decreased, and self-assurance increased significantly over the sessions. Undesired reversible side effects were documented in 10.9% of cases. These findings suggest that repeated practice of ILA, particularly with different syringe systems, enhances anesthetic success and psychological readiness for patient interaction. Additional training sessions may further improve proficiency.

Simulation of container discharge dynamics using modified cellular automata

In the field of physical logistics, efficient and precise control of material flow during the emptying of containers such as silos and wagons is crucial. This study introduces a not conventional cellular automaton model to simulate spillage from containers. The model is implemented using Excel macros, providing a user-friendly and accessible platform for logistics professionals. By modifying the traditional cellular automaton framework, the simulation can accurately represents the dynamics of material flow during container emptying processes. The proposed method allows for fine-tuned control over the spillage by integrating specific constraints and parameters, enhancing operational efficiency and reducing material loss. The versatility of the model makes it applicable to a wide range of logistical scenarios, demonstrating its potential as a valuable tool in physical logistics management.

Research on Control of Pump and Valve Testing Equipment

Abstract The complex flow state of the fluid makes it difficult for the pump valve to accurately control it. A study was conducted on the pressure flow control of a valve control device for gas-liquid two-phase flow, and experiments were conducted on the joint control of gas-liquid two-phase flow. The results showed that pressure has a significant impact on control, and it is necessary to ensure that pressure remains constant during the control process. The joint control of gas-liquid two-phase flow has consistency in changes, and precise control of gas-liquid two-phase flow can be achieved through studying consistency.

Robust control based on type-2 fuzzy logic for permanent magnet synchronous motor (PMSM)

This paper introduces a novel control technique utilizing the orientation of stator flux based on type 2 fuzzy controllers to control the mechanical power generated by a permanent magnet synchronous motor and addressing parametric variation challenges to enhance robust performance against external fluctuations. The Permanent Magnet Synchronous Motors driven by stator variables via two converters relies on these components to interface with the electrical network in distinct manners. The network-side converter facilitates continuous bus control and enhances power factor, while the motor-side converter enables precise control and optimization of energy flow during motor operation. The paper outlines the motor and converter models, followed by the development of control commands to regulate mechanical power (speed, torque) for optimal efficiency and production quality and we will then present a comparative study between the developed controls to highlight the best performing and most robust of each, . Numerical simulations demonstrate the effectiveness of implementing type 2 fuzzy logic control in achieving these objectives.

Particle motion under turbulent eddies: Inspiration for fine minerals flotation

Turbulent flow ubiquitous in flotation machines and contain multi-scale eddies. Compared to static environments, turbulence can increase particle kinetic energy and promote particle-bubble collision in mineral flotation. However, there have been few quantitative studies on turbulent eddies that affect particle motion, which limits the precise flow control of flotation processes. In this study, the motion characteristics of particles in isotropic turbulence were measured by particle tracking velocimetry, and the relationship between turbulent eddy and particle motion was quantitatively analyzed by 7-scale wavelet transform and fast Fourier transform. The measurement results show that the particle moves upward following a rotating turbulent eddy, and turbulent eddies with sizes of 35–119 µm and 127–288 µm drives the motion of dp = 74 µm and dp = 200 µm particles respectively. The turbulent acceleration of particles within a turbulent eddy can be calculated as aλ=Cε2/3λ-1/3. This study provides an eddy control basis for mineral flotation performance improvement.

Evaluation of cavitation phenomena in three-way globe valve through computational analysis and visualization test

A three-way valve has a multi-port structure with three openings, which allows control of the fluid direction. However, owing to the complicated trim shape of the internal flow, an irregular fluid flow occurs, which hinders precise fluid flow control. In severe cases, cavitation induces mechanical damage owing to abrupt changes in the fluid direction. In this study conducted a computational fluid dynamics (CFD) analysis was performed to estimate the localized cavitation around the bottom plug of the three-way valve. To quantify localized cavitation, the percentage of cavitation (POC) was derived using the vapor volume fraction (VVF). The POC, defined by the cavitation occurrence zone with VVF > 0.5 divided by the volume of the cavitation danger zone, was 34.90%. Cavitation at this POC level could cause mechanical damage; therefore, a size optimization was performed. The lengths of the optimized waist and tail regions of the bottom plug were obtained wherein the POC level decreased by 19.06%. In addition, experiments were conducted using a flow visualization test setup. The experimental results were quantified into the POC employing the image gradients method, and the results were in good agreement with the CFD analysis.

Research on Plug-in Hybrid Electric Vehicle (PHEV) Energy Management Strategy with Dynamic Planning Considering Engine Start/Stop

The key to improving the fuel economy of plug-in hybrid electric vehicles (PHEVs) lies in the energy management strategy (EMS). Existing EMS often neglects engine operating conditions, leading to frequent start–stop events, which affect fuel economy and engine lifespan. This paper proposes an Integrated Engine Start–Stop Dynamic Programming (IESS-DP) energy management strategy, aiming to optimize energy consumption. An enhanced rule-based strategy is designed for the engine’s operating conditions, significantly reducing fuel consumption during idling through engine start–stop control. Furthermore, the IESS-DP energy management strategy is designed. This strategy comprehensively considers engine start–stop control states and introduces weighting coefficients to balance fuel consumption and engine start–stop costs. Precise control of energy flow is achieved through a global optimization framework to improve fuel economy. Simulation results show that under the World Light Vehicle Test Cycle (WLTC), the IESS-DP EMS achieves a fuel consumption of 3.36 L/100 km. This represents a reduction of 6.15% compared to the traditional DP strategy and 5.35% compared to the deep reinforcement learning-based EMS combined with engine start–stop (DDRL/SS) strategy. Additionally, the number of engine start–stop events is reduced by 43% compared to the DP strategy and 16% compared to the DDRL/SS strategy.

Finite element method for natural convection flow of Casson hybrid (Al2O3–Cu/water) nanofluid inside H-shaped enclosure

The fundamental problem in electronic cooling systems is the implementation of a cavity such that it can be used to provide localized cooling to specific components, such as CPUs or GPUs, enhancing their performance and longevity. It can also be used in microfluidic devices for controlled drug delivery, where precise control of fluid flow is crucial. The present article numerically explores the free convection non-Newtonian Casson hybrid nanofluid phenomena that occur within an H-shaped cavity while heated from the middle. The heating efficiency and heat flow in a cavity are influenced by perpendicular hot walls that connect two vertical closed channels. A numerical solution is obtained by implementing the Galerkin finite element method to solve the partial differential equation. The numerical outcomes are depicted on the contour of streamlines and isotherms for different parameters in the following ranges: 0.1 ≤ η ≤ 0.4, 0.005≤ϕhp≤0.020, 0.1 ≤ γ ≤ 2, and 103 ≤ Ra ≤ 106 at fixed Pr = 6.2. In addition, line graphs show rate of heat transfer within the enclosure using the average Nusselt number for these parameters. Increased aspect ratios (η = 0.4) result in a minimal rate of heat transfer enhancement, whereas decreasing η leads to a significantly higher average Nusselt number and maximum heat transfer within the cavity. The convective rate of heat transfer increases with the presence of hybrid nanoparticles inside an H-shaped cavity for all Rayleigh numbers. The rotation of the Casson hybrid nanofluid also rises as the volume ratio of nanoparticles increases. For a fixed aspect ratio (A.R) of 0.1, the heat dissipation is 6.91% at a lower ϕhp value of 0.005 at a fixed Ra value of 105. However, it increases to 7.072% for a higher ϕhp value of 0.02 at Ra = 105. With increasing Ra number, ϕhp, and γ, the number NuAve increases.

Modeling and Control of Multi‐Stack Fuel Cell Air System based on Nonlinear Model Predictive Control Method

Hydrogen is crucial for achieving SDGs by driving energy transition and combating climate change. Proton exchange membrane fuel cell technology, leveraging hydrogen, faces challenges in meeting high‐power demands. The multistack fuel cell system (MFCS) tackles this by integrating multiple substacks, yet its air supply needs meticulous control. Proportional integral derivative (PID) decoupling from single‐stack falls short of MFCS. This article proposes nonlinear model predictive control (NMPC) for optimized air flow and pressure decoupling. Modeling MFCS's air system and designing a predictive model, it is aimed to ensuring precise control of air flow and pressure in each substack. The decoupling experiments show that NMPC outperforms PID, accurately managing air flow and pressure and reducing load fluctuations. For air mass flow, NMPC cuts mean‐absolute error (MAE) by 64.56% and root‐mean‐square error (RMSE) by 81.36%. For pressure, MAE drops 81.23% and RMSE 83.59%. Comprehensive step load tests confirm NMPC's precise, dynamic regulation too, compared to PID, NMPC lowers average MAE for air mass by 20.67%, pressure by 32.22%. RMSE improvements of 31.08% and 33.23% highlight NMPC's strength. NMPC's quick response mitigates coupling issues, enhancing vehicle load adaptability.

Surface charge-dependent slip length modulates electroosmotic mixing in a wavy micromixer

This study explores electroosmotic mixing in microfluidic channel with predefined surface topology, mainly focusing the effect of surface charge-dependent slip length on the underlying mixing dynamics. Our analysis addresses the need for precise control of flow and mixing of the participating fluids at microscale, crucial for medical and biomedical applications. In the present work, we consider a wavy microchannel with non-uniform surface charge to explore the electroosmotic mixing behavior. To this end, adopting a finite-element approach, we numerically solve the Laplace, Poisson–Boltzmann, convection–diffusion, and the Navier–Stokes equations in a steady-state. The model is validated by comparing the results with the available theoretical and experimental data. Through numerical simulations, the study analyzes electroosmotic flow patterns in microchannels, highlighting the impact of surface charge-dependent slip lengths on mixing efficiency. For example, at a diffusive Peclet number of 200, mixing efficiency drops from 95.5% to 91.5% when considering surface charge-dependent slip length. It is established that the fluid rheology, characterized by Carreau number and flow behavior index, non-trivially influences flow field modulation and mixing efficiency. Increased Carreau numbers enhance flow velocity, affecting overall mixing of the constituent fluids in the chosen fluidic pathway. For instance, by increasing the Carreau number from 0.01 to 1.0, a discernible trend emerges with higher flow line density and accelerated velocity within the microchannel. The study also examines the effect of diffusive Peclet numbers on the mixing efficiency, particularly in the convective regime of underlying transport. These insights offer practical guidance for designing microfluidic systems intended for enhanced mixing capabilities. Additionally, the study explores the likelihood of particle aggregation under shear forces, vital in biological non-Newtonian fluids, with implications for drug delivery, diagnostics, and biomedical technologies.

Bidirectional DC-DC Converter and Improved Electrical Vehicle Dynamic Response Control

Background: In automotive applications where bidirectional power flow is necessary to lighten the power system, dual active bridge (DAB) converters are frequently employed. Variations in the required output voltage, erratic input voltage, and shifting loads all have an impact on this converter. As a result, converter performance has to be improved. To increase efficiency, the current stress of the DC-DC converter must be optimised. This paper proposes a control scheme for the coupled inductor bidirectional DC-DC (CIB DC-DC) converter utilising both model predictive control (MPC) and a proportional-integral (PI) controller. The integration of these control techniques aims to enhance the performance and efficiency of the converter. Methods: The MPC algorithm is employed to predict the converter's future behaviour based on a dynamic model, taking into account system constraints and performance criteria. By optimising the control action over a finite time horizon, the MPC algorithm ensures an optimal response, considering the current state and anticipated changes. Additionally, a PI controller is incorporated to augment the control strategy. The proportional component of the PI controller enables a fast initial response to the error between the desired and actual converter outputs. The integral component eliminates steady-state errors and provides robustness against disturbances, resulting in improved overall system performance. Results: The proposed control scheme is implemented and evaluated through simulations and experimental tests on a prototype converter. The results demonstrate the effectiveness of the combined MPC and PI controller approach. Conclusion: The coupled inductor bidirectional DC-DC (CIB DC-DC) converter using MPC can provide precise control of power flow between two voltage domains, enabling efficient bidirectional power transfer. The predictive capabilities of MPC allow it to adapt to varying load conditions and respond quickly to changes, ensuring stable operation and accurate regulation of voltage and current. Overall, the coupled inductor bidirectional DC-DC converter controlled using MPC over PI offers improved performance, efficiency, and flexibility compared to traditional control methods. MPC can handle the complex dynamics response and non-linear characteristics of the converter, making it suitable for bi-directional vehicle charging applications, where precise control and high efficiency can be achieved.