1. Introduction

Mechatronics technology plays a crucial role in the current automotive manufacturing industry. By integrating multiple technologies, it drives the automotive industry towards energy conservation, environmental protection, and meeting personalized market demands, leading to significant changes in vehicle design and production methods [1,2]. For example, the integration of electro-hydraulic hybrid systems enhances energy efficiency by optimizing power distribution, while self-powered sensors contribute to improved vehicle safety and real-time monitoring, enabling better detection of potential hazards and ensuring more reliable performance under various driving conditions [3,4]. However, the high cost of mechatronics components and potential reliability issues under different driving conditions remain significant challenges. Despite advancements in technological innovation via existing research, cost-effectiveness and long-term performance have not been fully addressed. Therefore, this paper seeks to optimize the application of mechatronics technology in automotive manufacturing by concentrating on lowering component costs and enhancing system reliability. These issues directly impact the competitiveness of the automotive industry, and due to the lack of in-depth research in these areas, they warrant further exploration. By analyzing existing literature, it provides practical strategies for automotive manufacturers to improve production efficiency and product quality, thereby supporting the sustainable development of the automotive industry.

2. Fundamentals of mechatronics

2.1. The definition and core concepts of mechatronics

Mechatronics technology integrates mechanics, electronics, computing, and automation to optimize interdisciplinary systems for intelligent, automated, as well as efficient products [5]. By seamlessly combining sensing, control, actuation, and information processing, it enhances mechatronic systems with intelligence, precision, and adaptability, overcoming the limitations of traditional mechanical systems [5]. A typical mechatronic system is composed of a mechanical body, sensors, controllers, and actuators, all of which work together to meet the demands of complex industrial applications. In automobile manufacturing, the Anti-lock Braking System exemplifies mechatronics technology. It uses sensors to continuously monitor tire conditions, comparing real-time data with standard values to enhance braking performance. The controller then adjusts the braking torque based on the sensor feedback to prevent wheel lock-up, thus enhancing braking safety and vehicle stability [1]. Besides, mechatronics technology plays a crucial role in Advanced Driver Assistance Systems and Electronic Stability Control systems, among other applications. Its integration has significantly improved the safety, comfort, and reliability of automobiles, further accelerating the intelligent development of modern automotive manufacturing technology.

2.2. Key technological components of mechatronics systems

Mechatronic systems rely on the synergy of sensing, information processing, automatic control, and servo drive technologies to boost intelligence and operational efficiency. In particular, sensing and detection technology, often referred to as the “sensory organ” of mechatronic systems, continuously monitors system status and external conditions, converting collected data into electrical or digital signals for subsequent processing and control decisions [6]. In the automotive industry, sensors, such as speed, pressure, and temperature sensors, are widely used in engine management, braking, and chassis control systems. For example, sensors in electronic stability control systems capture real-time data on wheel speed, yaw rate, and steering angle, enabling the controller to make precise stability adjustments. In addition, information processing technology, as the brain of mechatronic systems, analyzes sensor data to support decision-making and enhance system adaptability. With advances in computer technology and artificial intelligence (AI) algorithms, mechatronic systems can now handle fault diagnostics, predictive maintenance, and intelligent decision-making [7]. In advanced driver assistance systems, information processing technology integrates data from LiDAR, millimeter-wave radar, and cameras, leveraging deep learning algorithms to assess the surrounding environment in real time. This enables features such as pedestrian detection, lane-keeping assistance, and automatic emergency braking (AEB), significantly improving driving safety. Automatic control technology ensures autonomous operation by dynamically adjusting actuators based on predefined objectives and real-time feedback [1]. It commonly employs proportional-integral-derivative (PID) control, fuzzy control, and artificial neural networks (ANN) to enhance response speed and stability. In electronic fuel injectionsystems, automatic control precisely regulates fuel injection timing and volume to optimize combustion, improving engine performance and fuel efficiency. Similarly, in adaptive cruise control systems, it adjusts speed based on preceding vehicles’ velocity and distance for safer, more efficient driving. At the execution level, servo drive technology converts electrical or hydraulic energy into precise mechanical motion [8]. Mechatronic systems use electric, hydraulic, or pneumatic servo drives for various applications. In EPS systems, they adjust torque based on driver input and vehicle dynamics for better steering. In industrial robotics, they enable precise motion planning, automation, and tasks like assembly, welding, and material handling.

3. The application of mechatronics technology in automotive manufacturing

3.1. The application in automotive power and transmission systems

In modern automotive power systems, mechatronics technology integrates sensors, microprocessors, and actuators to achieve precise fuel injection and ignition control, enhancing engine performance while reducing fuel consumption and emissions. The EFI system employs sensors to continuously monitor key engine parameters such as speed, load, and intake volume. A microprocessor processes this data to determine the optimal fuel injection quantity, ensuring precise fuel delivery [2]. This control strategy optimizes the air-fuel mixture and improves combustion efficiency, boosting engine power output and fuel economy. Moreover, modern ignition control systems leverage mechatronics technology to replace traditional mechanical ignition methods, overcoming limitations such as low precision and component wear. By processing real-time engine data, the microprocessor optimizes ignition timing and precisely regulates ignition through electronic modules, enhancing combustion efficiency and engine stability [2]. The integration of EFI and ignition control systems improves engine torque and power output while reducing emissions. These mechatronic advancements drive automotive power systems toward higher efficiency and environmental sustainability. In automatic transmissions (AT, CVT, DSG), mechatronic systems use sensors to continuously monitor real-time parameters such as engine speed, vehicle speed, and load. A microprocessor computes the optimal shift timing and strategy, while electronic actuators precisely execute the gear changes [1,2]. In addition, drive wheel slippage on slippery roads can significantly reduce vehicle stability, increasing the risk of skidding and loss of control. This technology enables the ASR system to continuously monitor wheel speed and driving conditions. Upon detecting slippage, it swiftly adjusts torque or applies braking to restore stability [2]. By improving vehicle control in challenging road conditions, ASR enhances both safety and driving comfort.

3.2. The application in automotive brake systems

Brake systems are vital to vehicle safety, and the integration of mechatronics technology has greatly enhanced braking response, stability, and intelligence, ensuring superior performance in emergency situations. The anti-lock braking system (ABS) employs wheel speed sensors to monitor rotational speed in real time. Upon detecting wheel lock-up, the system adjusts brake pressure to optimize slip ratio (10%-20%), maximizing tire-road friction [9,10]. This ensures shorter braking distances while allowing the driver to maintain steering control, preventing vehicle instability caused by wheel lock-up. The electronic stability control (ESC) system further enhances vehicle maneuverability and stability. By analyzing data from sensors measuring steering input, lateral acceleration, and yaw rate, ESC detects oversteer or understeer conditions. It then selectively applies braking to specific wheels or adjusts engine torque to counteract instability, helping the vehicle maintain its intended trajectory [11]. ESC is particularly crucial in high-speed cornering, slippery road conditions, and emergency maneuvers, significantly reducing the risk of accidents. The brake-by-wire (BBW) system replaces mechanical and hydraulic components with electronic sensors and actuators, ensuring faster, more precise braking [8]. This innovation improves energy recovery efficiency while enhancing vehicle dynamic stability, providing a more reliable braking solution for intelligent driving.

3.3. The application in automotive intelligent driver assistance systems

Advanced Driver Assistance Systems (ADAS) are integral to modern automotive intelligence, with mechatronics technology playing a pivotal role in environmental perception, driver monitoring, and active intervention. These systems not only enhance driving safety but also serve as a foundation for the development of autonomous vehicles. The laser-ranging radar system, strategically mounted at the front and rear of the vehicle, continuously scans the surrounding environment, measuring the distance and relative speed of nearby objects with high precision. The collected data is processed by an intelligent controller, which enables features such as collision warnings, adaptive cruise control, and emergency braking assistance [1]. By enhancing real-time awareness, this system minimizes collision risks and improves vehicle adaptability in complex conditions, advancing autonomous driving. The Driver Monitoring System (DMS) utilizes AI, facial recognition, and eye-tracking to evaluate attentiveness and detect fatigue or distraction. Upon detecting unsafe driving behavior, the system issues real-time alerts to prompt corrective actions, thereby mitigating the risks associated with driver inattention [7]. The continuous data collected by DMS contributes to the development of human-machine collaboration models, which are essential for the transition to fully autonomous driving. By combining perception, decision-making, and safety intervention, it enhances the driver assistance system, making them intelligent co-pilots for safer and more efficient driving.

3.4. The application in the automotive manufacturing process

In automotive manufacturing, mechatronics technology has driven the advancement of intelligent production, improving efficiency, quality control, and resource optimization. Intelligent robots are widely used in tasks such as precision assembly, quality inspection, and automated welding. These robots integrate mechanics, electronics, control, and computing technologies to perform complex operations with high precision and consistency, reducing human error and enhancing production quality [12]. Additionally, their deployment in hazardous environments minimizes risks for workers, improving workplace safety. The Intelligent Speed Assistance (ISA) system is an advanced safety feature increasingly integrated into modern vehicles. Previous studies demonstrated that ISA has notably reduced speeding rates in urban environments. For example, a trial conducted on London buses demonstrated that ISA reduced the speeding rate from 14.9%-17.8% to just 1%-3.3%, significantly lowering the risk of speed-related accidents [13]. Besides, the Internet of Things (IoT) and big data analytics are transforming automotive manufacturing by enabling intelligent process management. IoT enables real-time data exchange, creating an interconnected production network. Big data analytics optimize scheduling, resource use, and quality consistency through data analysis [5]. And the adoption of these technologies is propelling the automotive industry towards a more efficient, cost-effective, and intelligent manufacturing ecosystem.

4. Advantages and challenges of mechatronics technology in automotive manufacturing

4.1. Major advantages

The integration of mechatronics technology in automotive manufacturing has markedly improved vehicle performance, production efficiency, and intelligence, aligning with the growing demand for efficiency, safety, and smart mobility. The EFI and ignition control systems precisely regulate fuel injection and ignition timing, increasing combustion efficiency and power output while minimizing energy consumption [14]. In terms of driving safety, the ABS and BBW system profoundly enhance braking performance and vehicle stability. ABS prevents wheel lock-up, ensuring that the vehicle maintains steering control during emergency braking, while BBW further refines brake control for faster and more precise braking response [9]. Besides, automatic transmissions and anti-slip control systems improve transmission efficiency and driving stability by preventing wheel slip during startup, acceleration, or operation on slippery roads, thereby enhancing vehicle handling [8].

The implementation of intelligent driver assistance systems further accelerates the development of automotive intelligence. Laser radar systems continuously monitor the surrounding environment, accurately measuring the distance to obstacles and providing critical data for adaptive cruise control, collision warnings, and obstacle avoidance. By leveraging image recognition and sensor technology, the DMS continuously monitors drivers’ physiological states and behaviors, detecting fatigue or distractions in real time. It enhances driving safety through timely alerts, laying the groundwork for autonomous driving technology [7].

Moreover, the integration of mechanics, electronics, and information technology in mechatronics enhances vehicle intelligence. The synergy of multiple sensors and advanced algorithms enables precise environmental perception and intelligent decision-making. In autonomous driving scenarios, vehicles collect data through sensors, which are processed by intelligent algorithms to achieve autonomous navigation, path planning, and driving control, ultimately enhancing driving experience and road safety.

4.2. Challenges faced

The advancement of mechatronics technology in automotive manufacturing presents several notable challenges, including technical integration, cost, reliability, and talent shortages. Differences in system interfaces and data protocols can result in transmission errors and compatibility problems. For instance, mismatched sensor and controller interfaces in BBW system integration can interfere with braking signal transmission, potentially compromising performance [8]. Thus, establishing standardized industry protocols for interfaces and data transmission is essential to ensure seamless system integration.

The interdisciplinary nature of mechatronics requires expertise across multiple fields, yet the shortage of specialized talent hampers technological integration [5]. To tackle this issue, companies should focus on improving cross-disciplinary training, strengthening partnerships between industry and academia, and developing professionals with a wide range of technical expertise. Additionally, high-precision mechatronics equipment, like the LiDAR-based driver assistance system, comes with substantial costs [7]. Increasing R&D investment, promoting domestic production, and reducing dependence on imported equipment can help lower costs. Furthermore, the growing complexity of systems amplifies reliability risks, as the failure of a single component can compromise the entire system's functionality. For instance, a faulty ABS sensor may cause system failure, compromising driving safety. To ensure operational stability, it is important to optimize system design, enhance component reliability, and adopt predictive maintenance strategies [9].

In addition, the automotive industry faces challenges in attracting multidisciplinary professionals due to limited salary competitiveness and suboptimal working conditions, leading to talent attrition [5]. Consequently, it is imperative to optimize compensation packages, improve working conditions, foster strategic university-industry collaborations for specialized talent development, and enhance internal training programs to align with the dynamic demands of the industry.

5. Future development trends

The integration of mechatronics in the automotive industry, driven by advancements in AI, IoT, and big data, has significantly enhanced intelligence and automation. Autonomous driving technology will keep advancing, improving safety and traffic flow [5]. Future progress should prioritize data harmonization, algorithm enhancement, and system resilience to boost efficiency and reliability. Meanwhile, rising environmental and energy demands are reshaping the automotive industry, with mechatronics playing a vital role in increasing efficiency and cutting emissions. In the future, increased investment in the R&D of energy-saving technologies and sustainable materials is needed, along with policy support to promote green technologies. As demand for personalized vehicles rises, the need for customized production grows, supported by mechatronics technology. By enabling modular design, manufacturers can adapt production processes to meet consumer needs, improving efficiency while minimizing complexity and costs. Future efforts should prioritize standardizing data security and privacy protection, adopting advanced encryption technologies, and integrating intelligent manufacturing systems to optimize production, enhance efficiency, and improve product quality.

6. Conclusion

The study demonstrates that mechatronics technology has markedly improved vehicle performance, production efficiency, and intelligence in the automotive manufacturing field, thus promoting the sustainable development of the industry. However, issues like data transmission protocol differences and equipment malfunctions during system integration still impact the normal operation of the system. Additionally, the high cost of precision equipment, reliability risks from increased system complexity, and difficulties in fault diagnosis hinder widespread adoption, while talent shortages remain a significant challenge. Due to the reliance on literature review and lack of empirical validation, future research should focus on interdisciplinary collaboration, integration challenges, and system reliability. Besides, increasing R&D investment to reduce equipment costs and enhance economic efficiency, addressing talent development, and improving industry attractiveness are also essential. Future studies should include empirical analysis to investigate new technologies in real production, guiding automotive manufacturers and supporting sustainable industry development.