According to the Market Statsville Group (MSG), the global hardware-in-loop testing market size is expected to grow from USD 835.22 million in 2022 to USD 2,177.08 million by 2033, at a CAGR of 9.1% from 2023 to 2033. Vehicle modernization with advanced features such as Advanced Driver-Assistance Systems (ADAS), cameras, and radar increases the complexity of embedded control systems. Furthermore, the complexity is increased when one electronic control unit (ECU) in a vehicle equates to a massive number of signals representing various functions and I/O types. HIL simulation and testing are used to reduce test overhead and catastrophic schedule impacts in order to overcome this comprehensive test coverage challenge. These factors are expected to drive market growth. However, reluctance to invest due to the additional costs required for dedicated HIL hardware and software is a factor impeding the growth of the hardware-in-the-loop market. Furthermore, the market's high adoption in a wide range of applications, such as power and industrial robotics, acts as an opportunistic factor to propel growth during the forecast period. On the other hand, high cost of ownership and complexity in technology implementation had hapmered the market growth for the forecast period.
HIL testing entails simulating vehicle and environmental inputs for the electronic control unit (ECU) under test, causing it to believe that it is reacting to real-world driving conditions on the open road. The HIL bench includes all of the necessary vehicle components. A simulator sends signals to actual cameras and radar systems, which then send signals back to the system under test to see if it responds correctly to the inputs. HIL testing can simulate hundreds or thousands of scenarios without the time and expense of physical road tests. HIL testing allows for scenarios that would be too dangerous or inconvenient to test on the road.
Engineers use hardware-in-loop (HIL) to bridge the gap between using MIL (models-in-the-loop or software component models) and building a car, truck, or airplane for each test engineering lab. The ECU communicates with a vehicle via analogue, digital, and bus (or messaging) inputs and outputs, it can be physically tested by generating and consuming these electrical signals while putting "hardware in the loop" to simulate the vehicle. HIL enables ECU design engineers to collaborate on an engine controller alongside the mechanical team building the engine.
The COVID-19 originally began in Wuhan (China) around December 2019 and since then it has grown at a quick speed across the globe. In terms of confirmed cases and reported deaths, the United States, Brazil, India, Russia, France, the United Kingdom, Turkey, Italy, and Spain are among the worst impacted nations. Due to lockdowns, travel bans, and commercial shutdowns, the COVID-19 has had an impact on economies and businesses in a number of nations. The closure of numerous facilities and factories has disrupted global supply lines and harmed the global manufacturing economy. The COVID-19 had negatively affected the GDP growth of both developed and developing economies due to the global lockdowns and trade restrictions. The HIL market cannot experience the individual impact of the COVID-19 pandemic due to its widespread implementation in so many products and services. Flight cancellations, travel bans, quarantines, restaurant closures, restrictions on all indoor and outdoor events, and a significant slowdown in the supply chain were all the result of various governments' counteractions around the world. Other consequences of the pandemic included increased public fear, stock market volatility, a drop in business confidence, and future uncertainty. While trade in some goods and services shrank dramatically, it expanded dramatically in others. Post-Covid the market flourished as many companies started to incorporate hardware-in-loop testing to test and analyze in order to manage their operations efficiently.
The automobile industry is witnessing a tremendous growth over due to the growing technological advancements along with the ongoing initiatives by market players to grab several autonomous techniques embedded in vehicles. To make vehicles safer and more convenient, automakers are relying on stronger technologies and exploring a plethora of ways to improve the driving experience. Owing to consumer concerns about safety, the demand for HIL is increasing in order to make vehicles more comfortable and secure for them. Automobiles are incorporating technologies such as autonomous driving, advanced driver assistance systems, and collision avoidance systems to improve safety and ride comfort. ECUs, algorithms, and software used in autonomous technology are subjected to hardware in the loop testing.
Hardware in the loop is a difficult technique to implement as designing the mathematical model can be difficult depending on the variables and function blocks added to the system. Complex systems, such as microgrids, aircraft models, and automobile environment generation, necessitate heavy data processing hardware. This necessitates an initial investment in costly real-time simulators and rack computers to run the simulation model. As a result, when a manufacturer wants to set up hardware in the loop test system, purchasing a new system is expensive, and complex programmes are required to set up the simulation model. With the increasing complexity of embedded controller design, the demand for compatible hardware in the loop system has increased. The hardware in the loop system must be designed and programmed to meet the needs of the user. Because the goal and the device being tested have changed, the specifications of the hardware in the loop system must be changed so that it can simulate an environment that is very close to the real conditions; thus, it is not possible to create a standard programme for all applications. For instance, an automobile manufacturer's programming of the hardware in the loop system to ensure product conformance to the controller area network (CAN) will be quite different from that of an aerospace manufacturer testing its aerospace control systems. This task necessitates extensive knowledge and training.
With the advancement of network technologies and the Industrial Internet of Things (IIoT) in the direction of Industrial 4.0, Industrial Edge Computing enables an automation platform that can be accessed directly from the cloud. As a result, various wireless network-controlled robot platforms can now be used in industrial production. During the deployment process and design stage of a robot platform in an industrial facility, simulation and testing of various communication conditions are usually required to ensure the robustness and adaptability of the robotic system. A common solution for simulation is to introduce delays or other communication characteristics into the controller codes to mimic the impact of the network. However, modelling and simulating practical communication conditions, particularly wireless networks, is extremely difficult. Hardware-in-Loop (HiL) simulation is a simulation technology that uses computer modelling to simulate one part of the entire system while using physical modelling or an actual system for the other. Moreover, the demand for hardware in the loop testing technique in the power electronics sector has increased in recent years, particularly for testing the operation, stability, and fault tolerance of electrical grids. It’s use in the robotics industry to test complex controllers used in robots. The need for manufacturers to meet industry safety standards is also creating growth opportunities for loop hardware.
The study categorizes the hardware-in-loop testing market based on type and application area at the regional and global levels.
Based on the type, the market is bifurcated into closed loop HIL and open loop HIL. The closed loop HIL segment is expected to dominate the market share in 2022 in the global hardware-in-loop testing market. Closed-loop testing refers to tests, where the outputs of the system under test (SUT) are used as inputs to a plant and the outputs of the plant are used as inputs to the SUT, forming a closed control loop. Close loop HIL will dominate the market for its constant feedback that allows a certain variables such as the stress rate and the load rate to remain as a specified throughout the tests. A feedback loop in universal testing machines with closed-loop control systems continually conveys information from the closed-loop controller to the motor and from the motor to the closed-loop controller. Closed-loop systems provide higher accuracy due to the ability to react immediately to possible changes.
Based on the regions, the global hardware-in-loop testing market has been segmented across North America, Europe, Asia-Pacific, Middle East & Africa, and South America. Asia Pacific is projected to account the highest market share in 2022. The rising of the automotive, aerospace, and power electronics industries has contributed to the market's expansion. The automobile industry manufactured a total of 22.93 million cars, which included Passenger Vehicles, Commercial Vehicles, Three Wheelers, Two Wheelers, and Quadricycles. India has a substantial presence in the worldwide heavy vehicle market, since it is the world's largest tractor producer, second-largest bus maker, and third-largest heavy truck manufacturer. Subaru (Japan) and TATA Motors are two Asian automakers who use the hardware in the loop approach (India). Due to increasing of these industry had increased the demand for hardware-in-loop testing market for the forecasting period.
The hardware-in-loop testing market is extremely cutthroat, and significant competitors in the sector are using strategies including product launches, partnerships, acquisitions, agreements, collaboration, and growth to enhance their market positions. Most sector businesses focus on increasing their operations worldwide and cultivating long-lasting partnerships.
Frequently Asked Questions
Want to Review Complete Market Research Report
Budget constraints? Get in touch with us for special pricing
Request for Special PricingCustomize this Report
Related Reports
Student Loan Servicing Market 2022: Industry Size, Emerging Trends, Regions, Growth Insights, Opportunities, and Forecast By 2033
Mar 2024Lab Automation Market 2021: Industry Size, Regions, Emerging Trends, Growth Insights, Development Scenario, Opportunities, and Forecast by 2027
Mar 2024Retail Automation Market 2022: Industry Size, Regions, Emerging Trends, Growth Insights, Opportunities, and Forecast By 2030
Mar 2024Mobility As A Service (Maas) Market 2023: Industry Size, Emerging Trends, Regions, Growth Insights, Opportunities, and Forecast By 2033
Mar 2024Web 3.0 Blockchain Market 2022: Industry Size, Emerging Trends, Regions, Growth Insights, Opportunities, and Forecast By 2033
Mar 2024