About this role
Division R&D Department ARAS, CS & Validation Level EX Functional Area Control Strategy 1 Job Title Vehicle Control Software Development 2 Reporting Functional reporting to: General Manager, R&D 3 Background i) Educational Qualification Essential: B.Tech / M.Tech in Mechanical / Mechatronics / Automobile / Electrical (with strong control & system dynamics background) ii) Experience Minimum: 3 Maximum: 7 4 Job Role & Responsibilities Role: Vehicle Control Software development Technical/ Functional: Responsible for designing and developing control software and control strategies for vehicle systems across Powertrain, Braking, Chassis, Body, Hybrid & Electric vehicle domains. Developing Model Based Design (MBD) solutions using MATLAB, SIMULINK & STATEFLOW as per system and software requirement specifications. Generating production-quality C code using Auto Code Generation tools such as dSPACE TargetLink / MathWorks Embedded Coder. Performing Model-in-Loop (MiL), Software-in-Loop (SiL) validation and unit-level testing. Integration of generated C code with Base OS, task scheduling, and real-time execution validation. Development and integration of CAN Interface Layer, followed by full system integration testing. Vehicle-level Testing & Validation of control software on prototype and production-intent vehicles. Calibration and tuning of performance parameters using tools such as INCA, CANape, etc. Vehicle data acquisition and analysis using tools such as BUSMASTER, CANoe, etc. Preparation and maintenance of software documentation, control strategy documentation, and requirement traceability. 5 Competency Requirements Specific expertise required for functional area: Strong understanding of vehicle control systems, control theory, and dynamic systems. Sound knowledge of Powertrain systems (ICE/HEV/EV), Braking Systems (ABS/ESP), and Vehicle Dynamics. Multi-disciplinary understanding of vehicle electronics, sensors & actuators, ECUs, powertrain and chassis systems. Sound knowledge of CAN-BUS communication, diagnostic concepts, and vehicle network architecture. Strong hands-on experience with MATLAB, SIMULINK, STATEFLOW. Strong hands-on with auto-code generation tools such as TargetLink, Embedded Coder. Hands-on vehicle calibration and validation experience is mandatory. Good understanding of Model-in-Loop (MiL) and Software-in-Loop (SiL) testing practices. Awareness of software development best practices, source code management (SVN, Git), and CI/CD workflows. Python scripting knowledge for automation and data processing is an added advantage. Strong mechanical systems intuition: torque generation, driveline dynamics, etc. 6 Likely sources Continental, Eaton, Tata Technologies, Bosch, Daimler Truck Innovation Centre India, MBRDI, L&T, Ather, Ola Electric, KPIT, AVL.