Sensing the Future: A Closer Look at Automotive Sensors and Their Impact

If we were to pick the most important driver of transformation in the automotive industry, most certainly it will be the software. Whether is ADAS, autonomous driving, connected mobility or the EVs, software is the real disruptor here.

A report by Mckinsey predicts that by 2030, the global automotive software and electronics market will be almost $460 billion.

While we give most of the credit for this disruption to software, a worthy companion to software is often left out. We are talking about the sensors.

Automotive software relies on vast amounts of vehicular data streaming continuously to them. For instance, an intelligent battery management system requires battery parameters such as voltage, current, temperature at every instance to keep the EV running. Such parameters are captured by various sensors fitted inside the vehicle.

Autonomous driving is a prime example in which sensors such as LIDAR and cameras work in all their glory. Multiple complex IoT sensors collect and send a stream of vast data packets for the software to process in real time.

The advancement in sensors and automotive software has gone hand in hand. Naturally so, because great software needs accurate data to process, and an advanced sensor is as important as the software processing this data.

In this blog, we will look at automotive sensors in this light and try to deep dive into their use-cases, capabilities, and future. So, let’s start with the major types of sensors used in automotive industries.

Most Deployed Automotive Sensors and Their Impact on Mobility

1. Vehicle Speed Sensor

The Vehicle Speed Sensor, also known as Wheel Speed Sensor, continuously monitors the rotational speed of one or more wheels. Leveraging magnetic or Hall effect technology, it generates electrical pulses proportionate to wheel speed.

The ECU captures this data and applies it to crucial systems like Anti-lock Braking (ABS), Traction Control (TCS), and Electronic Stability Control (ESC).

As a result, drivers experience optimal braking performance, enhanced stability during cornering, and improved vehicle traction on slippery surfaces.

2. Engine Speed Sensor

The Engine Speed Sensor, also referred to as Crankshaft Position Sensor, records the rotational speed of the engine’s crankshaft. Using Hall effect or magneto-resistive technology, it converts the mechanical motion into electrical signals.

This data is critical for engine management, precisely controlling fuel injection timing, ignition timing, and synchronization.

The ESS empowers engines to operate efficiently, achieve optimal fuel consumption, and reduce harmful emissions.

3. Pressure Sensor

Pressure sensors are deployed across various vehicle systems to monitor fluid pressures. They employ different technologies like piezoresistive or capacitive to convert pressure into electrical signals.

The ECU interprets these signals to ensure proper engine oil pressure, fuel system pressure, and tire pressure.

By monitoring these vital parameters, pressure sensors contribute to engine health, fuel efficiency, and tire safety, ultimately enhancing overall vehicle performance.

4. In-Car Air Quality Sensors

Air Quality Sensors constantly monitor the air inside the vehicle. Using cutting-edge technology, these sensors detect pollutants and harmful gases like carbon monoxide and nitrogen dioxide.

The inner mechanism of these sensors is mostly based on either light scattering technology, electrodes to detect the pollutants or humidity and temperature sensors.

• Particulate Matter (PM) Sensors: PM sensors rely on light scattering techniques. They emit a light beam through the air, and when fine particles (dust, pollen, soot) pass through the beam, it scatters, creating a measurable change in light intensity. By analysing the scattered light, the sensor quantifies the concentration of particulate matter, providing real-time data on air pollution levels.
• Gas Sensors: Gas sensors employ different techniques based on the target gas. For example, electrochemical gas sensors use electrodes immersed in a specific electrolyte to detect gases like carbon monoxide (CO) and nitrogen dioxide (NO2). When these gases come in contact with the electrodes, a chemical reaction occurs, resulting in a measurable electrical current, which indicates gas concentration.
• Humidity and Temperature Sensor: Humidity and Temperature Sensors utilize capacitive or resistive techniques to measure the ambient conditions inside and outside the vehicle cabin. They continuously monitor humidity levels and temperature, providing data to the ECU and the HVAC system. This enables automatic climate control, i.e., adjusting heating, cooling, and ventilation settings based on the occupants’ preferences and external weather conditions. As a result, passengers experience a comfortable and pleasant cabin environment regardless of external climate variations.

Infotainment screen showing air quality data captured by sensors

The Dynamic Interplay of Sensors and Software in Modern Automobiles

While the sensors handle the data capturing part, it is the algorithms that process the data into actions. Each sensor continuously collects data and sends electrical signals, varying in voltage or frequency, to the Electronic Control Unit (ECU). The ECU acts as the vehicle’s brain, equipped with advanced software that interprets the incoming sensor data in real-time. The software algorithms process the data to make informed decisions and trigger corresponding actions.

Sample these automotive functionalities:

1. Adaptive Cruise Control (ACC): Utilizing VSS and radar sensors, ACC maintains a safe distance from the vehicle ahead, adjusting speed as traffic conditions change.
2. Rain-Sensing Wipers: Humidity and light sensors detect rain, automatically activating wipers and adjusting their speed based on the intensity of rainfall.
3. Engine Start-Stop System: Engine Speed Sensor enables automatic engine shutdown when the vehicle comes to a stop, saving fuel, and restarting when the driver releases the brake pedal.
4. Tire Pressure Monitoring: Pressure sensors in the tires monitor pressure levels, and the software alerts the driver when pressure drops below the recommended level. This enhances driver safety and extends tire life.
5. Dynamic Stability Control: VSS and other sensors provide data to ESC, ensuring the vehicle maintains stability during abrupt maneuvers. This prevents skidding or loss of control.

Now let’s pick one of the most relevant automotive systems, keeping the rising pollution levels in mind – air quality monitoring and improvement. Taking a deep dive into the inner workings of this system will help us understand the synergy between automotive sensors and automotive software.

We have already mentioned that air quality sensors detect pollutants such as particulate matter, harmful gases and other volatile compounds.

The captured data from the cabin air quality sensors is transmitted to the vehicle’s Electronic Control Unit (ECU), where air quality monitoring and improvement systems come into play. The software’s central role is to interpret the sensor data and take appropriate actions to ensure a healthy cabin environment:

• Air Quality Monitoring: The software continuously analyses the sensor data to assess air quality parameters. It categorizes the data into different pollutant levels and triggers alerts if pollutant concentrations exceed predefined safety thresholds.
• HVAC System Integration: The Heating, Ventilation, and Air Conditioning (HVAC) system is closely integrated with the software. Based on sensor data, the HVAC system adjusts fan speed, air circulation, and filtration settings to optimize air quality inside the cabin.
• Air Quality Improvement: To combat high pollutant levels, the software may activate the recirculation mode, preventing external air intake and filtering the cabin air through advanced filtration systems (like HEPA filters) to remove contaminants.
• In-Cabin Alerts: In cases of elevated pollutant levels, the software notifies the driver and passengers through visual or audio alerts, prompting them to take necessary actions like rolling up windows or adjusting HVAC settings.

A Quick Overview of Sensor Integration with Automotive Software

In order to achieve seamless integration between automotive sensors and software, various algorithms need to be developed. These algorithms are designed to process sensor data, make intelligent decisions, and control the vehicle’s systems effectively.

Here are some key algorithms that need to be developed for successful sensor-software integration:

• Signal Processing Algorithms: These algorithms are responsible for processing raw sensor data and converting it into meaningful information. For example, in the case of the Vehicle Speed Sensor (VSS), signal processing algorithms analyze the electrical pulses from the sensor and calculate the vehicle’s speed based on the pulse frequency and timing.
• Filtering Algorithms: Filtering algorithms are used to remove noise and unwanted artifacts from sensor data. They ensure that the software receives accurate and reliable information from the sensors, thereby enhancing the overall system’s performance and accuracy.
• Data Fusion Algorithms: In modern vehicles, multiple sensors work together to provide comprehensive information about the vehicle’s surroundings. Data fusion algorithms combine data from different sensors, such as cameras, radars, and ultrasonic sensors, to create a unified and accurate perception of the vehicle’s environment.
• Control Algorithms: These algorithms take the processed sensor data and determine the appropriate actions or responses. In the example of the Anti-lock Braking System (ABS), control algorithms decide when and how to modulate brake pressure to prevent wheel lock-up during sudden braking.
• Machine Learning Algorithms: Machine learning algorithms are increasingly used in automotive systems to enable advanced driver-assistance features and autonomous driving capabilities. These algorithms learn from historical sensor data and can make predictions and decisions based on patterns and trends. This enhances the vehicle’s responsiveness and adaptability to various driving conditions.
• Adaptive Control Algorithms: Adaptive control algorithms continuously adjust the vehicle’s systems based on changing conditions. For instance, adaptive cruise control systems use sensor data to maintain a safe following distance from the vehicle ahead, adjusting the speed as necessary.
• Fault Detection and Diagnostics (FDD) Algorithms: FDD algorithms monitor sensor outputs and detect anomalies or sensor failures. They play a crucial role in ensuring the safety and reliability of the vehicle’s systems, especially in critical functions like braking and steering.

Concluding Thoughts

In the ever-evolving world of automotive technology, sensors stand tall as the worthy companion of automotive software.

With each passing day, sensors become smarter, more precise, and seamlessly integrated with cutting-edge software, elevating our driving experience to new heights. From preventing accidents through Anti-lock Braking Systems to enhancing cabin comfort with Air Quality Sensors, these sensors play a monumental role in shaping the future of mobility.

We at Embitel Technologies understand the complex world of automotive sensors and their integration with software. Whether it is the air quality monitoring system or adaptive automotive lighting, we have been ‘sensing the road ahead’ effectively for years.