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