Browse Topic: Hardware-in-the-loop (HIL)

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An Integrated Model Approach for Predicting Vehicle Dynamics Performance during HiL Validation2026-28-0044To be published on 02/01/2026
In the automotive industry, increasing noise regulations are influencing product sales and passenger comfort, creating a need for more effective noise testing methods. Hardware-in-Loop (HiL) based virtual acoustic testing serves as a critical step before Driver-in-Loop testing, allowing for the assessment of noise levels inside and outside the vehicle under various conditions before real-world testing is performed. This study addresses the conversion of a physical vehicle model in the AMESim environment into FMU-RT (Linux) format, and the translation of a powertrain control system from Simulink to C++ code. Key challenges in the FMU-RT conversion include the integration of appropriate submodels for each component and enabling the interfaces necessary for SCANeR and virtual acoustic testing. In the C++ code conversion, challenges involved configuring the correct parameters, ensuring the model runs at a fixed time step and sampling time of 1 ms, and resolving issues related to the
visuvamithran, Rishikesan, CHOUGULE, Sourabh, Srinivasan, Rangarajan, LAURENT, Nicolas
Advancing Automotive Radar Characterization: OTA HIL Testing for Enhanced ADAS Safety2026-26-0043To be published on 01/16/2026
The increasing demand for reliable Advanced Driver-Assistance Systems (ADAS) and autonomous driving technologies necessitates the precise validation of automotive radar sensors. Traditional on-road testing, while effective, presents challenges such as limited repeatability, high costs, and safety concerns. To address these limitations, this paper introduces an Over-the-Air (OTA) Hardware-in-the-Loop (HIL) methodology for radar characterization, providing a controlled and repeatable lab-based validation approach. This methodology enables dynamic testing of key radar parameters, including range estimation, angle of arrival measurement, Doppler velocity analysis, and object detection accuracy. The proposed setup supports diverse testing scenarios, such as variable target distances, relative speeds, multiple object simulation, and environmental effects, ensuring a comprehensive evaluation of radar behaviour under complex and safety-critical conditions. Through OTA testing, developers can
Jadhav, Tejas, Karle, Ujjwala, Paul, Harshit, SNV, Karthik
Hardware in Loop Validation of Rotary Switch with TFT Display2026-26-0540To be published on 01/16/2026
The increasing complexity of modern automotive drive control systems necessitates the adoption of robust validation methods to ensure functional safety, reliability and customer satisfaction. This paper presents the development and implementation of a comprehensive Hardware-in-the-Loop (HIL) testing framework designed specifically for a specific ECU known as Gear Selection Switch (GSS)/Drive control switch (DCS) system. Hardware-in-the-Loop (HIL) Testing is a simulation-based testing technique where real physical hardware (like an electronic control unit, switch or sensor) is tested by connecting it to a virtual simulation of the rest of the system — instead of testing it inside a real vehicle. Following the analysis of all the field failure incidents reported till date for GSS, detailed root cause investigations were conducted using in-house testing and Ishikawa diagram analysis. A critical failure mode was identified and addressed through targeted mechanical design modification and
Bhuyan, Anurag, Jahagirdar, Shweta, Khandekar, Dhiraj
Next Gen Automotive EDS Architecture Design Verification using Real-Time Function Mode Simulation and Failure Condition Analysis2026-26-0454To be published on 01/16/2026
In current automotive electrical design practices, simulation and functional verification of the Electrical Distribution System (EDS) at the design stage are largely absent. Typically, the validation of controller behaviour and EDS wiring is performed only during HIL, SIL, MIL, prototype testing, or physical vehicle trials, often revealing issues late in the development cycle. This delay leads to costly redesigns, prolonged timelines, and increased chances of failure during vehicle integration. Therefore, there is a critical need for an early-stage simulation methodology that ensures robust EDS and controller design, enabling "first-time-right" readiness at the design stage itself. The proposed simulation framework introduces a function mode-based structural approach, where individual vehicle functions are mapped to their corresponding electrical circuits within the vehicle’s wiring system. Resistance values are allocated to specific paths depending on the active function or
Jaisankar, Gokulnath, Warke, Umakant, CHAKRA, PIPUN, Borole, Akash
Proactive AI-Enhanced Cybersecurity for Next-Gen Automotive Infotainment ECU2026-26-0619To be published on 01/16/2026
Abstract With the rapid advancement of connected vehicle technologies, infotainment Electronic Control Units (ECUs) have become central to user interaction and connectivity within modern vehicles. However, this enhanced functionality has introduced new vulnerabilities to cyberattacks. This paper explores the application of Artificial Intelligence (AI) in enhancing the cybersecurity framework of infotainment ECUs. The study introduces AI-powered modules for threat detection and response, presents an integrated architecture, and validates performance through simulation using MATLAB, CANoe, and NS-3. This approach addresses real-time intrusion detection, anomaly analysis, and voice command security. Key benefits include zero-day exploit resistance, scalability, and continuous protection via OTA updates. The paper references real-world automotive cyberattack cases such as Tesla's OTA vulnerability patches, BMW ConnectedDrive exploits, and Jeep Cherokee's Uconnect hack, emphasizing the
More, Shweta, Kulkarni, Shraddha, Kumar, Priyanshu, GHANWAT, HEMANT, Joshi, Vivek
Shaping the Future of Mobility with Innovative Power Tailgate Testing Solutions2026-26-0473To be published on 01/16/2026
Abstract With increasing demand for automation and user convenience in modern vehicles, Power Operated Tailgates (POT) have become standard in premium and mid-segment cars. However, validating such systems—comprising electronic control units (ECUs), sensors, actuators, and mechanical components poses significant challenges in safety, reliability, and cost. This paper introduces a Hardware-in-the-Loop (HiL) based validation framework that allows comprehensive, automated, and safe testing of POT systems without depending on full vehicle prototypes. The HiL platform integrates Real Time Hardware and Real Time software with dynamic models to simulate real-world behaviors. It enables automated validation of normal and fault scenarios—such as open/close commands, anti-pinch protection, voltage sensitivity, and communication errors—ensuring robust system performance. The proposed framework accelerates development, improves test coverage, and supports early fault detection, making it a
More, Shweta, GHANWAT, Hemant, Shetti, Suraj, Jape, Akshay, Kulkarni, Shraddha, Jagdale, Nitin
Testing Framework and Safety Evaluation for Vehicle-to-Vehicle (V2V) Charging Systems in Electric Mobility2026-26-0176To be published on 01/16/2026
As the adoption of electric vehicles (EVs) accelerates, innovative charging strategies like Vehicle-to-Vehicle (V2V) charging are gaining attention for their potential to offer emergency energy support and decentralized charging options. Particularly in countries like India, where the charging infrastructure is still maturing, V2V charging can play a vital role in extending operational range and enhancing user convenience in fleet and remote applications. This paper proposes a structured testing framework to evaluate the functionality, safety, communication protocols, and energy transfer efficiency of V2V systems. Emphasis is placed on real-time testing using HIL simulations, thermal behavior under load transfer, fault detection, and protection mechanisms. The framework supports OEMs and integrators in validating reliable, scalable V2V solutions aligned with future EV interoperability standards.
Uthaman, Sreekumar, Mulay, Abhijit B
SEooC-Based Design Framework for Integrated EV Power Conversion Systems under ISO 26262 Compliance2026-26-0192To be published on 01/16/2026
The rapid integration of electric vehicle (EV) power conversion elements—such as traction inverters, onboard chargers, and DC-DC converters—into unified architectures poses new challenges for ensuring functional safety compliance as per ISO 26262. This paper presents a system-level framework that leverages the Safety Element out of Context (SEooC) approach to design and validate reusable safety-critical components independent of vehicle-specific applications. By defining clear assumptions of use and ASIL decomposition strategies, the proposed method facilitates early-stage fault analysis and verification. The framework integrates model-based development with Hardware-in-the-Loop (HIL) testing and formal verification techniques to validate both control logic and hardware behavior under diverse fault injection scenarios. The result is a scalable, standards-compliant methodology that reduces time-to-market and enhances reliability in integrated EV power electronics platforms. The work
Uthaman, Sreekumar, Mulay, Abhijit B, Gadekar, Pundlik
Model Standardization for MBD Throughout Entire Power Unit Development Process2026-26-0428To be published on 01/16/2026
The distribution of mobility equipped with electrified power units is advancing towards carbon-neutral society. The electrified power units require an integration of numerous hardware components and large-scale software to refine high-performance system. Additionally, a value-enhancement cycle of mobility needs to be accelerated more than ever. The challenge is to achieve high-quality performance and efficient development using Model-Based Development (MBD). The development process based on V-model has been applied to electrified power units in passenger vehicle. Traditionally, MBD has been primarily utilized in the left bank (performance design phase) of the V-model for power unit development. MBD in performance design phase has been widely implemented in research and development because it refines prototype performance and reduces the number of prototypes. However, applying MBD to the entire power unit development process, from performance design phase to performance verification
Ogata, Kenichiro, Katsuura, Akihiro, Tsuji, Minako, Matsumoto, Takumi, Iwase, Hiromu, Nakasako, Seiya, TAKAHATA, Motoki
Human-Centric Automotive Interior Lighting assessment: A feedback-Based Approach2026-26-0132To be published on 01/16/2026
Automotive interior lighting systems must comply with rigorous internal standards while aligning with evolving customer expectations across diverse vehicle segments. As technological advancements accelerate and consumer demands grow, these systems have become increasingly advanced. Traditionally, validation relied on physical integration with vehicle and its hardware particularly silver box unit and infotainment systems. However, this conventional approach presents several limitations, including dependency on mature hardware and software, challenges in testing and synchronization across multiple lighting modules, and constraints in design validation accuracy. To address these limitations, this paper introduces an innovative approach that employs real-time hardware-in-the-loop (HIL) simulation for digital lamp testing. This method facilitates autonomous and abuse testing, enabling independent validation of interior lighting systems within a controlled virtual environment while
Shah, Kunal, Joshi, Vivek S., Mandloi, Prince
NN FMU: Deep Learning Models for Next-Gen xiL Vehicle Simulation2026-26-0452To be published on 01/16/2026
Functional Mock-up Units (FMUs) have become a standard for enabling co-simulation and model exchange in vehicle system development. However, traditional FMUs derived from physics-based models can be computationally intensive, especially in scenarios requiring real-time performance. This paper presents a Python-based approach for developing a Neural Network (NN) based FMU using deep learning techniques, aimed at accelerating vehicle simulation while ensuring high fidelity. The neural network was trained on vehicle simulation data and developed using Python frameworks such as TensorFlow. The trained model was then exported into FMU, enabling seamless integration with FMI-compliant platforms. The NN FMU replicates thermal behavior of vehicle with high accuracy while offering a significant reduction in computational load. Benchmark comparisons with Physical Thermal Model demonstrate that the proposed solution provides both efficiency and reliability across various driving conditions
Srinivasan, Rangarajan, ASHOK BHARDE, Pooja, MHETRAS, Mayur, CHEHIRE, Marc
Automating Fault Detection Time Interval in Automotive Functional Safety Using HIL Simulation2025-28-027411/06/2025
Functional safety is driven by number of standards like in automotive its driven by ISO26262, in Aerospace its driven by DO-178C, and in Medical its driven by IEC 60601. Automotive electronic controllers must adhere to state-of-the-art functional safety standard provided by ISO26262. A critical functional safety requirement is the Fault Handling Time Interval (FHTI), which includes the Fault Detection Time Interval (FDTI) and Fault Reaction Time Interval (FRTI). The requirements for FHTI are derived from Failure Mode Effect Analysis (FMEA) conducted at the system level. Various fault categories are analyzed, including electrical faults (e.g., short to battery, short to ground, open circuits), systemic faults (e.g., sensor value stuck, sensor value beyond range), and communication faults (e.g., incorrect CAN message signal values). Controllers employ strategies such as debouncing and fault time maturity to detect these faults. Numerous FDTI requirements must be verified to ensure
Lengare, Sunil, Yadav, Vikaskumar, Shiraskar, Pallavi
Leveraging AI for Autonomous Vehicle Simulations in SIL and HIL Frameworks2025-28-027111/06/2025
This paper offers recent ideas and its implementation on leveraging AI for off highway Autonomous vehicle Simulations in SIL and HIL frameworks. Our objective is to enhance software quality and reliability while reducing costs and efforts through advanced simulation techniques. We employed multiple innovative solutions to build a System of Systems Simulation. Physics based models are a prerequisite for detailed and accurate representation of the real-world system, but it poses challenges due to its computational complexity and storage requirements. Machine learning algorithms were used to create surrogate/reduced order models to optimize by preserving the expected fidelity of models. It helped to speed up simulation and compile model code for SIL & HIL Targets. Built AI driven interfaces to bridge windows, Linux and Mobile Operating systems. Time synchronization was the key challenge as multiple environments were needed for end-to-end solutions. This was resolved by reinforcement
Karegaonkar, Rohit P., Aole, Sumit, Dasnurkar, Swapnil, Singh, Vishwajeet, Saha, Soumyadeep
Model-Based Software Engineering: Physics Coupled with Software for Test Case Reuse Across the V Cycle2025-01-044709/16/2025
The development of cyber-physical systems necessarily involves the expertise of an interdisciplinary team – not all of whom have deep embedded software knowledge. Graphical software development environments alleviate many of these challenges but in turn create concerns for their appropriateness in a rigorous software initiative. Their tool suites further enable the creation of physics models which can be coupled in the loop with the corresponding software component’s control law in an integrated test environment. Such a methodology addresses many of the challenges that arise in trying to create suitable test cases for physics-based problems. If the test developer ensures that test development in such a methodology observes software engineering’s design-for-change paradigm, the test harness can be reused from a virtualized environment to one using a hardware-in-the-loop simulator and/or production machinery. Concerns over the lack of model-based software engineering’s rigor can be
McBain, Jordan
Validating Modular Applications in the FACE and GCIA Architectures2025-01-047609/16/2025
Ground vehicle software continues to increase in cost and complexity, in part driven by tightly integrated systems and vendor lock-in. One method of reducing costs is reuse and portability, encouraged by the Modular Open Systems Approach and the Future Airborne Capability Environment (FACE) architecture. While FACE provides a Conformance Testing Suite to ensure portability between compliant systems, it does not verify that components correctly implement standard interfaces and desired functionality. This paper presents a layered test methodology designed to ensure that a FACE component correctly implements working communication interfaces, correctly handles the full range of data the component is expected to manage, and correctly performs all of the functionality the component is required to perform. This testing methodology includes unit testing of individual components, integration testing across multiple units, and full hardware in the loop system integration testing, offering a
Lingg, Michael, Paul, Howard, Sullivan, Kyle, VanSolkema, William
Method to Analyze Driving Dynamics during Faults in the Electric Drivetrain on a Vehicle-in-the-Loop Test Bench2025-24-012309/07/2025
The mechanical components of drive systems for electric vehicles are less complex than those of conventional drives and are therefore generally less prone to faults. On the other hand, a challenge lies in the relatively limited experience in dealing with faults in the electric drivetrain and their effects on driving dynamics compared to conventional drives. To meet these challenges, this paper presents a method to simulate faults in the electric powertrain of a real demonstrator vehicle on a full vehicle test bench and to evaluate the influence on driving dynamics. For this purpose, the demonstrator vehicle was modeled in detail in a co-simulation between the driving dynamics simulation software CarMaker and the real-time solution for simulating and testing electrical components Typhoon HIL. This enabled the investigation of the vehicle’s behavior in the event of a fault. Subsequently, tests with the vehicle were performed on the Vehicle-in-the-Loop full vehicle test bench and the
Rautenberg, Philip, Konzept, Anja, Hitz, Arne, Frey, Michael, Reick, Benedikt
Building an In-House SIL Framework: Key Design Choices, Features, and Performance Evaluation2025-24-001809/07/2025
Nowadays, Software-in-the-Loop (SIL) represents a crucial methodology in the development and validation of control systems, particularly in sectors such as automotive, marine, and aerospace. It involves creating a virtual representation of a real environment with varying levels of accuracy. Using SIL techniques, engineers can develop and test software in the early stages of the development cycle, reducing overall time-to-market and costs. Typically, to simulate complex control systems, a primary tool is used to manage and integrate an entire application-specific environment composed of application software, plants, sensors and actuators, and communication protocols. Although several commercial solutions are currently available on the market to support SIL activities, Dumarey Softronix wanted to explore the possibility of developing an in-house software tool to leverage the benefits of SIL. This paper provides a high-level overview of the main steps involved in developing a complete SIL
Mancuso, Claudio, Tesconi, Cristian, Autieri, Fabio
Methods for Estimating Coasting Resistance of Heavy-Duty Commercial Vehicles under Various Loads02-19-01-000508/19/2025
This research primarily addresses the issue of resistance model setting for chassis dynamometers or EIL (engine-hardware-in-the-loop) systems under various loads. Based on the data available from the heavy-duty commercial vehicle coast-down test reports, this article proposes three methods for estimating coasting resistance. For heavy-duty commercial vehicles that have not undergone the coast-down test, this article proposes the GA-GRNN (AC) model to predict coasting resistance. Compared to the GA-BPNN model proposed by previous studies, the new model, which achieves 93% prediction accuracy, demonstrates higher estimation accuracy. For heavy-duty commercial vehicles that have undergone the coast-down test, the coasting equal power method proposed in this article can estimate the coasting resistance under various loads. The accuracy and stability of the new method are verified by several coast-down tests. Compared to the existing method proposed by existing scholars, the new method has
Liang, Xingyu, Sun, Shangfeng, Li, Tengteng, Zhao, Jianfu
Design of a Rapid Validation Platform for Model-Based Powertrain Control Strategies2025-01-505307/21/2025
In light of the growing intricacy and demand for control in power systems, model-based design (MBD) methodologies have become a prevalent approach in the development of control strategies. This paper proposes a rapid and comprehensive model-based verification platform for powertrain control strategies, with a particular focus on its capacity for seamless integration with MATLAB/Simulink models. The design of the field-programmable gate array (FPGA) enables the platform to perform general-purpose functions, including sensor signal acquisition, actuator driving, and data interaction. In a hardware-in-the-loop (HIL) test, the platform exhibits exemplary hardware driving performance and control strategy verification capability, which can markedly reduce the development cycle and reliance on external devices. This study offers a comprehensive and effective approach for the rapid development and assessment of power system control strategies, establishing a crucial foundation for advancing
Tan, Zhixue, Yang, Xinda, Li, Yunhua, Shen, Jiawei, Zhang, Jing, Liu, Hongyu, Shuai, Xiuyun, Zhao, Feiyang, Yu, Wenbin
SAE TOMORROW TODAY - Smarter Automotive Testing with AI and Simulation1352207/07/2025
The new test track isn't asphalt--it's AI and simulation. From hardware-in-the-Loop (HIL) to real-time performance analytics, new innovations are reshaping how vehicles are designed, validated, and brought to market. At the forefront of this transformation is A&D Technology, a leader in integrated test automation and lab management solutions for the transportation and energy markets. By integrating AI-driven analytics with high-fidelity simulation environments, the company is empowering automotive engineers to streamline testing workflows, reduce physical prototypes, and accelerate innovation in everything from EV powertrains to autonomous systems. To learn more, we sat down with Mike Uhl, President & CEO, to discuss how A&D Technology's work in simulation and test automation is helping engineers bring the next generation of mobility technologies to life. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget
Hineman, Marcie
Closed-Loop Real-Time Simulation of the Thermal and Electromagnetic Behavior in Electric Drive Trains: Optimizing Model Accuracy for Virtual Prototyping2025-01-032007/02/2025
This paper presents a coupled electromagnetic and thermal simulation of Permanently Excited Synchronous Machines (PMSM) in the context of virtual prototyping in a real-time Hardware-in-the-Loop (HiL) environment. Particularly in real-time simulations, thermal influences are often neglected due to the increased complexity of a coupled simulation. This results in inaccurate simulations and incomplete design optimizations. The objective of this contribution is to enable a precise and realistic real-time simulation that represents the electromagnetic as well as the thermal behavior. The electromagnetic simulation is executed used a Field-Programmable Gate Array (FPGA) and parameterized by Finite Element Analysis (FEA) results. The thermal model is based on a Lumped-Parameter-Thermal-Network (LPTN), which is based on physical laws, geometry parameters and material specifications. The simulation results are validated with testbench measurements to ensure the accuracy of the overall model. By
Jonczyk, Fabian, Kara, Onur, Bergheim, Yannick, Lee, Sung-Yong, Strop, Malte, Prochotta, Fabian, Andert, Jakob
Methodology for Real-World Automated Function Development: From Virtual to On-Vehicle Implementation2025-01-028807/02/2025
The automotive industry is increasingly facing challenges stemming from growing system complexities, shortened development cycles, and the demand for rapid time-to-market transitions. Reinforcement learning (RL) has emerged as a promising approach to developing advanced control functions due to its adaptive and autonomous nature. The technique has already demonstrated its viability in virtualised X-in-the-Loop (XiL) environments. However, its application to real-world vehicle systems is inhibited by safety concerns, real-time constraints, and the integration into established software toolchains. This paper introduces a comprehensive methodology for developing practical control functions with RL: starting in a virtual environment, training then transitions to a Hardware-in-the-Loop (HiL) setup, and ultimately proceeds to a real vehicle. Utilising the open-source framework LExCI, the proposed approach facilitates seamless training across multiple development stages and showcases RL’s
Badalian, Kevin, Picerno, Mario, Lee, Sung-Yong, Schaub, Joschka, Andert, Jakob
Research on Road-Sense Simulation Algorithm and Analysis of Its Effect on Different Steering Wheels2025-01-875304/01/2025
With the continuous development of automotive intelligence, there is an increasing demand for vehicle chassis systems to become more intelligent, electronically controlled, integrated, and lightweight. In this context, the steer-by-wire system, which is electronically controlled, offers high precision and fast response. It provides greater flexibility, stability, and comfort for the vehicle, thus meeting the above requirements and has garnered widespread attention. Unlike traditional systems, the steer-by-wire system eliminates mechanical components, meaning the road feel cannot be directly transmitted to the steering wheel. To address this, the road feel, which is derived from the vehicle's state or integrated with environmental driving data, must be simulated and transmitted to the steering wheel through a road feel motor. This motor generates feedback that mimics the road feel, similar to that experienced in a conventional steering system. This simulation enhances the driver's
Li, Shang, Kaku, Chuyo, Zheng, Hongyu, Zhang, Yuzhou
High Performance Computer Based Software Defined Vehicle Hardware in the Loop Testing2025-01-813704/01/2025
Recent years have seen a strong move towards Software Defined Vehicles (SDV) concept as it is seen as an enabler for advancing the mobility by integrating complex technologies like Artificial Intelligence (AI) and Connected Autonomous Driving (CAD) into the vehicle. However, this comes with fundamental changes to the vehicle’s Electrical/Electronic (EE) architecture which require novel testing approaches. This paper presents FEV’s SDV Hardware-In- The-Loop (HIL) test setup which focuses on testing the developed HPC-based software. The functionality of the SDV HIL test setup is demonstrated by testing the software of multiple technologies within the High Performance Computer (HPC) environment like ADAS and teleoperation virtual control units with Over-the-air (OTA) up- dates capability. Test results show the effectiveness of utilizing FEV’s HIL setup in developing and validating the software of SDV platforms.
Obando, David, Alzu'bi, Hamzeh, Carreón Vásquez, Erwin, Alrousan, Qusay, Alnajdawi, Mohammad Sami, Tasky, Thomas
Real-Time PMV Thermal Comfort Index Observer Based on Artificial Neural Networks for Infrared Heating Panel Control2025-01-813904/01/2025
Improving electric vehicles’ range can be achieved by integrating infrared heating panels (IRPs) into the existing Heating Ventilation and Air-Conditioning system to reduce battery energy consumption while maintaining thermal comfort. Localized comfort control enabled by IRPs is facilitated by thermal comfort index feedback to the control strategy, such as the well-known Predicted Mean Vote (PMV). PMV is obtained by solving nonlinear equations iteratively, which is computationally expensive for vehicle control units and may not be feasible for real-time control. This paper presents the design of real-time capable thermal comfort observer based on feedforward artificial neural network (ANN), utilized for estimating the local PMV extended with IRP radiative heating effects. The vehicle under consideration is equipped with 12 heating panels (zones) organized into six controller clusters that rely on the average PMV feedback from its respective zone provided by a dedicated ANN. Each of six
Cvok, Ivan, Yerramilli-Rao, Isha, Miklauzic, Filip
Developing a Vehicle-in-Virtual-Environment (VVE) Based Autonomous Driving Function Development and Evaluation Pipeline for Vulnerable Road User Safety2025-01-806104/01/2025
Traditional methods for developing and evaluating autonomous driving functions, such as model-in-the-loop (MIL) and hardware-in-the-loop (HIL) simulations, heavily depend on the accuracy of simulated vehicle models and human factors, especially for vulnerable road user safety systems. Continuation of development during public road deployment forces other road users including vulnerable ones to involuntarily participate in the development process, leading to safety risks, inefficiencies, and a decline in public trust. To address these deficiencies, the Vehicle-in-Virtual-Environment (VVE) method was proposed as a safer, more efficient, and cost-effective solution for developing and testing connected and autonomous driving technologies by operating the real vehicle and multiple other actors like vulnerable road users in different test areas while being immersed within the same highly realistic virtual environment. This VVE approach synchronizes real-world vehicle and vulnerable road user
Chen, Haochong, Cao, Xincheng, Guvenc, Levent, Aksun Guvenc, Bilin
Development of a Computer-Less Robotic Platform for ADAS Testing2025-01-806404/01/2025
Testing collision avoidance systems on vehicles has become increasingly complex. Robotic platforms called Pedestrian Target Carriers (PTC) typically require Global Positioning System (GPS), network communications, tuning, and ever-increasing scope to the user interface to function. As an alternative to these complicated systems, but as an improvement to a pulley system pedestrian target carrier, a simplistic robotic platform was developed. An open-loop user interface was designed and developed, and a series of tests were performed to evaluate the effectiveness of the robot in performing basic, repeatable straight-line tests with a vehicle in the loop. Based on testing outcomes, the development of further control algorithms, user requirements, and the prototype improvements are analyzed for future work.
Bartholomew, Meredith, Muthaiah, Ponaravind, Heydinger, Gary, Zagorski, Scott
Modular Dynamometer Testing Framework to Evaluate Energy Impacts of Longitudinal Automated Driving Systems2025-01-806504/01/2025
As longitudinal Automated Driving System (ADS) technologies, such as Adaptive Cruise Control (ACC), become more prevalent, robust testing frameworks that encompass both simulation and vehicle-in-the-loop (VIL) methodologies are essential to ensure system reliability, safety, and performance refinement. Although significant research has focused on ACC algorithm development and simulation testing, existing VIL dynamometer testing frameworks are typically tailored to specific vehicle models and sensor simulation tools. These highly customized approaches often fail to account for broader interoperability while overlooking energy consumption as a key performance metric. This paper presents a novel modular framework for ACC dynamometer testing, designed to enhance interoperability across a diverse range of vehicle platforms, simulation tools, and dynamometer facilities with a focus on evaluating impacts of automated longitudinal control on the overall energy consumption of the vehicle. The
Goberville, Nicholas, Hamilton, Kayla, Di Russo, Miriam, Jeong, Jongryeol, Das, Debashis, Ord, David, Misra, Priyashraba, Crain, Trevor
The Development and Real-Time Application of DP-Based Optimized A-ECMS Algorithm for Multi-Mode Series-Parallel Hybrid Electric Vehicles2025-01-858904/01/2025
The hybrid electric drive system has the potential to make a significant contribution to the energy sustainability of the automotive industry. This paper investigates the improved adaptive equivalent consumption minimization strategy (A-ECMS) for a multi-mode series-parallel hybrid electric vehicle. First, a basic ECMS algorithm for the series-parallel vehicle is established, which considers the instantaneous optimal torque matching in the electric, serial hybrid, and engine driving modes. Under the condition that the future traffic information scenario is known, it is desired to realize the global optimal planning based on the combination of dynamic programming (DP) and ECMS. The SOC, engine speed, and torque results calculated by the DP strategy are used as benchmarks to develop the improved SOC-AECMS and S-AECMS strategies, which better incorporate the advantages of the global optimization results. Finally, a hardware-in-the-loop simulation platform is set up to validate the real
Zhu, Jingyu, Han, Mengwei, Liu, Chongfan, Yang, Chenfan, Nishida, Keiya
Research on Automatic Emergency Braking Pedestrian System Considering Road Adhesion Coefficient10-09-03-002203/08/2025
To further optimize the automatic emergency braking for pedestrian (AEB-P) control algorithm, this study proposes an AEB-P hierarchical control strategy considering road adhesion coefficient. First, the extended Kalman filter is used to estimate the road adhesion coefficient, and the recursive least square method is used to predict the pedestrian trajectory. Then, a safety distance model considering the influence factor of road adhesion coefficient is proposed to adapt to different road conditions. Finally, the desired deceleration is converted into the desired pressure and desired current to the requirements of the electric power-assisted braking system. The strategy is verified through the hardware-in-the-loop (HIL) platform; the simulation results show that the control algorithm proposed in this article can effectively avoid collision in typical scenarios, the safe distance of parking is between 0.61 m and 2.34 m, and the stop speed is in the range of 1.85 km/h–27.64 km/h.
Wang, Zijun, Wang, Liang, Ma, Liang, Sun, Yong, Li, Chenghao, Yang, Xinglong
Time-Varying Gain-Scheduled Path-Tracking Controller with Delay Compensation (TGDC) for Autonomous Vehicles10-09-02-001202/19/2025
Path-tracking control occupies a critical role within autonomous driving systems, directly reflecting vehicle motion and impacting both safety and user experience. However, the ever-changing vehicle states, road conditions, and delay characteristics of control systems present new challenges to the path tracking of autonomous vehicles, thereby limiting further enhancements in performance. This article introduces a path-tracking controller, time-varying gain-scheduled path-tracking controller with delay compensation (TGDC), which utilizes a linear parameter-varying system and optimal control theory to account for time-varying vehicle states, road conditions, and steering control system delays. Subsequently, a polytopic-based path-tracking model is applied to design the control law, reducing the computational complexity of TGDC. To evaluate the effectiveness and real-time capability of TGDC, it was tested under a series of complex conditions using a hardware-in-the-loop platform. The
Hu, XuePeng, Zhang, Yu, Hu, Yuxuan, Wang, Zhenfeng, Qin, Yechen
Angle-Weighted Time-to-Collision Algorithm for Enhanced Obstacle Avoidance in Autonomous Driving2025-01-702201/31/2025
To tackle the challenge of accurately predicting collision times for autonomous vehicles navigating complex dynamic obstacles, this paper proposes an innovative Angle-Weighted Time-to-Collision (AW-TTC) algorithm. Traditional TTC algorithms are known for their computational simplicity and strong real-time performance, making them widely applicable across various driving scenarios. However, they often struggle with predictive accuracy when encountering obstacles moving at angles, which can delay vehicle response and compromise overall safety. To address this limitation, this study introduces a modification to the traditional TTC algorithm by incorporating an angle-based weighting factor, improving collision time prediction accuracy. A Hardware-in-the-Loop (HIL) experimental setup was developed, utilizing a Vehicle Control Unit (VCU) and the SCANeR simulation platform to simulate dynamic obstacles in complex traffic scenarios. The AW-TTC algorithm’s performance was then evaluated
Zhu, Shaopeng, Tang, Yuanning, Li, Bing, Wang, Xiaoliang, Chen, Huipeng
Design And Bench Verification of PSO-Optimized Fuzzy PI Control Strategy for PMSM Based on UAV Flight Load Simulation2025-01-704901/31/2025
The development of the electrification technology of unmanned aerial vehicle (UAV) puts forward higher requirements for the control performance and verification methods of permanent magnet synchronous motor (PMSM). In this paper, a fuzzy PI control strategy based on a particle swarm optimization (PSO) algorithm is proposed to optimize the parameters of the PI controller and improve the dynamic response and control accuracy of PMSM. Firstly, Matlab/Simulink is used to build an online vector control model of PMSM, and the PSO algorithm is used to optimize the controller parameters online to adapt to the dynamic characteristics of the motor under different working conditions. Secondly, a current reconstruction scheme is designed, which reshapes the current waveform by sampling at the center point of the pulse width modulation (PWM) signal to make it closer to the ideal sine wave, so as to improve the motor operation efficiency. Finally, Speedgoat is used to build a HiL hardware in-loop
Du, Wentao, Zhu, Jingyu, Wang, Zhenyu, Wang, Chao, Geng, Heming, Liu, Kun
Modeling, Simulation and Hardware in the Loop Test of PEM Electrolysis System2025-01-709701/31/2025
PEM electrolysis system has characteristic of excellent performance such as fast response, high electrolysis efficiency, compact design and wide adjustable power range. It provides a sustainable solution for the production of hydrogen, and is well suited to couple with renewable energy sources. In the development process of PEM electrolysis controller, this article originally applied the V-mode development process, including simulation modeling, RCP testing, and HIL testing, which can provide guidance in the practical application of electrolytic hydrogen production. In this paper, we present modeling and simulation study of PEM water electrolysis system. Model of electrolytic cell, hydrogen production subsystem and thermal management subsystem are constructed in Matlab/Simulink. Controller model was designed based on PI control strategy. A rapid prototyping controller with MPC5744 chip was used to develop the control system of electrolytic hydrogen production system. Hardware in the
Hua, Yuwei, Jin, Zhenhua, Tian, Ying, Tao, Yuepeng
Self-Learning Method for Shift Hub Position in a Double-Input Shaft Hybrid Gearbox Using Linear Active Disturbance Rejection Control and Nutcracker Optimization Algorithm02-18-01-000401/07/2025
Due to manufacturing, assembly, and actuator wear, slight deviations between the actual and logical positions of various gears in a transmission system may accumulate, affecting shift quality, reducing shift accuracy, and causing operational anomalies. To address this issue, a self-learning method based on the top dead center (TDC) and lower dead center (LDC) was proposed, specifically for the hybrid gearbox of an electric torque converter (eTC) module and a double-input shaft gearbox (DIG). The linear active disturbance rejection control (LADRC) method was employed to estimate and manage the nonlinear resistance during the motion of the shifting motor. To simplify the controller parameter problem, the nutcracker optimization algorithm (NOA) was utilized to tune the LADRC parameters, thereby optimizing the position self-learning process. The control strategy was modeled using MATLAB/SIMULINK, and its reasonableness was verified through hardware-in-the-loop (HIL) tests. Based on these
Hong, Hanchi, Quan, Kangning, d’Apolito, Luigi, Xu, Li
Optimizing Search Testing Method for Brake Boost Degradation Based on Electrical Chassis System M-HIL Bench2024-01-705012/13/2024
With the technology of electronic chassis control systems of automobile is widely used, the functional interaction between brake system and the other electronic systems may lead to brake boost degradation. Therefore, it is necessary to find out brake boost degradation events in the quite large number of driving scenarios. To solve the difficulty of thoroughly and quickly searching for brake boost degradation conditions in the large number of driving scenarios, based on Mechatronic-Hardware-In-the-Loop (M-HIL) technology, this paper constructs an electrical chassis system M-HIL bench to verify the function and performance of the electronic brake control system under actual chassis system conditions. To search and locate the brake boost degradation conditions rapidly and enhance the searching efficiency of levels boundary of affecting factors for brake boost degradation, firstly, based on pair-wise coverage combinatorial testing, brake boost degradation occurrence rate is estimated and
Guo, Xiaotong, Li, Lun, Chen, Zhicheng, Zhang, Liliang, Yan, Luping, Wang, Wei, Zh, Bing
Research on the Pull Drift Compensation Control Algorithm based on Steer-By-Wire Systems2024-01-705212/13/2024
SBW(Steer-by-wire) is a steering system that transmits the driver’s request and gives feedback to the driver through electrical signals. This system eliminates the mechanical connection of the traditional steering system, and can realize the decoupling of the steering wheel and the road wheel. In addition, this system has a perfect torque feedback system, which can accurately and delicately feedback the road surface information to the driver. However, vehicle driving deviation is one of the most common failure modes affecting vehicle performance in the automotive aftermarket, this failure mode can exacerbates tire wear, reducing their life cycle, at the same time, the driver must apply a counter torque to the steering wheel for a long time to maintain straight-line travel during driving. This increases the driver’s operational burden and poses safety hazards to the vehicle’s operation. Based on the steer-by-wire system and vehicle driving deviation characteristics, this paper proposes
Xiangfei, Xu, Qu, Yuan
Implementation of a Hybrid Hardware-in-the-Loop (HIL) Test System for Automotive Software Validation and Verification2024-28-025212/05/2024
The automotive industry relies heavily on software to enhance safety, performance, and user experience. The increasing complexity of automotive software demands rigorous testing methodologies. Ensuring the quality and reliability of this software is critical. In this paper, an innovative approach to software validation and verification using a Hybrid Hardware-In-the-Loop (HIL) test system has been proposed. This methodology integrates diverse hardware and software tools to establish a flexible and efficient testing environment. HIL environment can evaluate Device Under Test (DUT) with minimal alterations. This comprehensive solution includes the development of test strategies, plant model simulation, and compliance assurance, all in accordance with automotive standards such as ASPICE, ISO26262. Introduction of a Personality module for Automotive ECU (DUT), enables testing of multiple products using the same HIL setup. This is achieved by loading a DUT-specific signal mapping
Yadav, Vikaskumar, Bhade, Nilesh
Deployment of Continuous Integration and Continuous Testing in Mobility for Software Qualification Test2024-28-019812/05/2024
In the rapidly evolving field of automotive engineering, the drive for innovation is relentless. One critical component of modern vehicles is the automotive ECU. Ensuring the reliability and performance of ECU is paramount, and this has led to the integration of advanced testing methodologies such as Hardware-in-the-Loop (HIL) testing. In conjunction with HIL, the adoption of Continuous Integration (CI) and Continuous Testing (CT) processes has revolutionized how automotive ECU are developed and validated. This paper explores the integration of CI and CT in HIL testing for automotive ECU, highlighting the benefits, challenges, and best practices. Continuous Integration and Continuous Test (CI/CT) are essential practices in software development. Continuous Integration process involves regularly integrating code changes into the main branch, ensuring that it does not interfere with the work of other developers. The CI/CT server automatically build and test code whenever a new commit is
Hande, Sheetal Vikram, Mandava, Balaji Bharath
Reinforcement Learning Based Intelligent Fan Controller2024-28-017612/05/2024
In Automotive world, vehicle development includes design and testing of hardware and software. Hardware includes components required for actuation and sensing, along with the controller hardware. Software includes control logic embedded in controller for functioning of these components. Generally, software inside controller could be validated in various ways e.g., Software in Loop (SiL), Hardware in Loop (HiL), Vehicle testing. During initial phase of control software development cycle, plant models with adequate accuracy replicating hardware components are utilized for digital software validation. Many a times, hardware components might be available before control software matures. Hence, to validate plant models for their accuracy & quality alternate option of actual controller is needed during initial phase. Intelligent controller mimicking original controller can be an alternate option for plant model improvement and component level performance analysis. This paper proposes a
Chhagar, Rohnit Singh, Navse, Siddharth, Kumar, Lavanya
Autonomous Landing of UAV in Non-Cooperative Environments Based on Fusion of Monocular and Stereo Depth Estimation2024-01-701911/15/2024
In non-cooperative environments, unmanned aerial vehicles (UAVs) have to land without artificial markers, which is a key step towards achieving full autonomy. However, the existing vision-based schemes have the common problems of poor robustness and generalization, and the LiDAR-based schemes have the disadvantages of low resolution, high power consumption and high weight. In this paper, we propose an UAV landing system equipped with a binocular camera to preform 3D reconstruction and select the safe landing zone. The whole system only consists of a stereo camera, and the innovation of the solution is fusing the stereo matching algorithm and monocular depth estimation(MDE) model to get a robust prediction on the metric depth. The whole landing system consists of a stereo matching module, a monocular depth estimation (MDE) module, a depth fusion module, and a safe landing zone selection module. The stereo matching module uses Semi-Global Matching (SGM) algorithm to calculate the
Zhou, YiBiao, Zhang, BiHui
Experimental Test Bench Showcasing an X in the Loop Strategy for Fuel Cell Testing2024-01-432211/05/2024
In the quest for reduced cost and shorter development times for fuel cell systems in industrial applications, two major issues arise. First, the electrochemical behavior of fuel cell systems is inherently difficult to predict. Second, testing fuel cell systems is resource intensive. These issues compound: Setting up an accurate model of a fuel cell system incurs long testing periods for model validation. Further, it does not guarantee acceptable results outside the tested range or for other membrane electrode assembly compositions. To mitigate these two major issues an X in the Loop concept is proposed. Essentially, this is the direct integration of the test sample, here a single fuel cell, into the modelling environment of the whole system. In practice, two strategies with different levels of integration are defined. The first strategy consists of initially deducing the operating parameters of the sample cell from the fuel cell system model. Then, setting them to the sample cell in
Oswald, Tancrède, Weiss, Lukas, Wensing, Michael
Integrated Motion Control Strategy Considering Parameter Robustness for Distributed Vehicle by Wire10-08-04-003110/10/2024
To address the issues of functional conflicts in execution subsystems and the deterioration of control performance due to model parameter uncertainties in the motion control of distributed vehicle by wire, this article proposes an integrated control strategy considering parameter robustness. This strategy aims to compensate for model mismatch, resolve functional conflicts, and achieve motion coordination. Based on the over-actuation characteristics of distributed vehicle by wire, this article constructs the dynamic model and utilizes the tire cornering properties along with phase portraits to delineate the working regions of the execution subsystems. To deal with model parameter uncertainties and mismatch, tube-based model predictive control (tube-based MPC) is applied to the control strategy design, which compensates for model deviations through state feedback and constructs a robust positively invariant set (RPI) to constrain the system state. Correspondingly, the weights of control
Chen, Guoying, Bi, Chenxiao, Zhao, Xuanming, Yang, Liunan, Tang, Zhuo, Yu, Huili
A Hardware-in-the-Loop Platform for Developing a Fuel Cell Hybrid Electric Microcar: Fuel Cell Stack Sizing Using a Real-Time Testing Approach2024-24-000609/18/2024
Sustainable mobility is a pressing challenge for modern society. Electrification of transportation is a key step towards decarbonization, and hydrogen Fuel Cell Hybrid Electric Vehicles (FCHEVs) offer a promising alternative to Battery Electric Vehicles (BEVs), especially for long-range applications: they combine a battery system with a fuel cell, which provides onboard electric power through the conversion of hydrogen. Paramount importance is then given to the design and sizing of the hybrid powertrain for achieving a compromise between high performance, efficiency, and low cost. This work presents a Hardware-in-the-Loop (HIL) platform developed for designing and testing the powertrain layout of an FCHEV. The platform comprises two systems: a simulation model reproducing the dynamics of a microcar and a hardware system for the fuel cell hybrid electric powertrain. The former simulates the vehicle's behavior, while the latter is composed of a 2kW real fuel cell stack and a 100Ah Li-ion
Bartolucci, Lorenzo, Cennamo, Edoardo, Cordiner, Stefano, Donnini, Marco, Grattarola, Federico, Mulone, Vincenzo
Real-Time Implementable Reduced-Order Energy Model for an Electric Vehicle14-14-01-000608/22/2024
Accurate estimation of vehicle energy consumption plays an important role in developing advanced energy-saving connected automated vehicle technologies such as Eco Approach and Departure, PHEV mode blending, and Eco-route planning. The present study developed a reduced-order energy model with second-order response surfaces and torque estimation to estimate the energy consumption while just relying on the drive cycle information. The model is developed for fully electric Chevrolet Bolt using chassis dynamometer data. The dyno test data encompasses the various EPA test cycles, real-world, and aggressive maneuvers to capture most powertrain operating conditions. The developed model predicts energy consumption using vehicle speed and road-grade inputs for a drive cycle. The accuracy of the model is validated by comparing the prediction results against track and road test data. The developed model was able to accurately predict the energy consumption for track drive cycles within the error
Goyal, Vasu, Dudekula, Ahammad Basha, Stutenberg, Kevin, Robinette, Darrell, Ovist, Grant, Naber, Jeffery
Test Cycle Simulation of Bench Based on Deep Reinforcement Learning15-17-03-001507/31/2024
Test cycle simulation is an essential part of the vehicle-in-the-loop test, and the deep reinforcement learning algorithm model is able to accurately control the drastic change of speed during the simulated vehicle driving process. In order to conduct a simulated cycle test of the vehicle, a vehicle model including driver, battery, motor, transmission system, and vehicle dynamics is established in MATLAB/Simulink. Additionally, a bench load simulation system based on the speed-tracking algorithm of the forward model is established. Taking the driver model action as input and the vehicle gas/brake pedal opening as the action space, the deep deterministic policy gradient (DDPG) algorithm is used to update the entire model. This process yields the dynamic response of the output end of the bench model, ultimately producing the optimal intelligent driver model to simulate the vehicle’s completion of the World Light Vehicle Test Cycle (WLTC) on the bench. The results indicate that the
Gong, Xiaohao, Li, Xu, Hu, Xiong, Li, Wenli
Neural Network Modeling of Black Box Controls for Internal Combustion Engine Calibration2024-01-299507/02/2024
The calibration of Engine Control Units (ECUs) for road vehicles is challenged by stringent legal and environmental regulations, coupled with short development cycles. The growing number of vehicle variants, although sharing similar engines and control algorithms, requires different calibrations. Additionally, modern engines feature increasingly number of adjustment variables, along with complex parallel and nested conditions within the software, demanding a significant amount of measurement data during development. The current state-of-the-art (White Box) model-based ECU calibration proves effective but involves considerable effort for model construction and validation. This is often hindered by limited function documentation, available measurements, and hardware representation capabilities. This article introduces a model-based calibration approach using Neural Networks (Black Box) for two distinct ECU functional structures with minimal software documentation. The ECU is operated on
Meli, Matteo, Wang, Zezhou, Bailly, Peter, Pischinger, Stefan
Fuel Cell Fault Simulation and Detection for on Board Diagnostics Using Real-Time Digital Twins2024-37-001406/12/2024
The modern automotive industry is facing challenges of ever-increasing complexity in the electrified powertrain era. On-board diagnostic (OBD) systems must be thoroughly calibrated and validated through many iterations to function effectively and meet the regulation standards. Their development and design process are more complex when prototype hardware is not available and therefore virtual testing is a prominent solution, including Model-in-the-loop (MIL), Software-in-the-loop (SIL) and Hardware-in-the-loop (HIL) simulations. Virtual prototype testing relying on real-time simulation models is necessary to design and test new era’s OBD systems quickly and in scale. The new fuel cell powertrain involves new and previously unexplored fail modes. To make the system robust, simulations are required to be carried out to identify different fails. Thus, it is imminent to build simulation models which can reliably reproduce failures of components like the compressor, recirculation pump
Pandit, Harshad Rajendra, Dimitrakopoulos, Pantelis, Shenoy, Manish, Altenhofen, Christian
Adaptive Model Predictive Control for Articulated Steering Vehicles2024-01-504204/12/2024
Vehicles equipped with articulated steering systems have advantages such as low energy consumption, simple structure, and excellent maneuverability. However, due to the specific characteristics of the system, these vehicles often face challenges in terms of lateral stability. Addressing this issue, this paper leverages the precise and independently controllable wheel torques of a hub motor-driven vehicle. First, an equivalent double-slider model is selected as the dynamic control model, and the control object is rationalized. Subsequently, based on the model predictive control method and considering control accuracy and robustness, a weight-variable adaptive model predictive control approach is proposed. This method addresses the optimization challenges of multiple systems, constraints, and objectives, achieving adaptive control of stability, maneuverability, tire slip ratio, and articulation angle along with individual wheel torques during the entire steering process of the vehicle
Huang, Bin, Ma, Minrui, Ma, Liutao, Cui, Kangyu, Wei, Xiaoxu
Multi-Contact Real-Time Tire Model Validation Using a Novel Hardware-in-the-Loop Simulator Apparatus2024-01-227504/09/2024
Simulators are essential part of the development process of vehicles and their advanced functionalities. The combination of virtual simulator and Hardware-in-the-loop technology accelerates the integration and functional validation of ECUs and mechanical components. The aim of this research is to investigate the benefits that can arise from the coupling of a steering Hardware-in-the-loop simulator and an advanced multi-contact tire model, as opposed to the conventional single-contact tire model. On-track tests were executed to collect data necessary for tire modelling using an experimental vehicle equipped with wheel force transducer, to measure force and moments acting on tire contact patch. The steering wheel was instrumented with a torque sensor, while tie-rod axial forces were quantified using loadcells. The same test set has been replicated using the Hardware-in-the-loop simulator using both the single-contact and multi-contact tire model. The simulation apparatus is composed of a
Veneroso, Luca, Capitani, Renzo, Alfatti, Federico, Annicchiarico, Claudio, Farroni, Flavio, Sakhnevych, Aleksandr
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