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In a math-based control algorithm design, model-based simulation and testing are very important as an integral part of design process. There are many advantages of using modeling and simulation in the algorithm design. In this paper, Algorithm-in-the-Loop and Hardware-in-the-Loop approaches are adopted for a transmission control algorithm development. A practical approach is introduced on how to test the control algorithms with a reliable plant (virtual engine, transmission, and vehicle) model in the closed-loop simulation. In using combination of open-loop and closed-loop simulations, various key behavior test cases are developed and documented for the success of control algorithms development. Secondly, the same test cases are reused and verified against the production codes, which are automatically generated from the math-based control algorithm models.

A math-based approach is now in use to reduce transmission control algorithm development time and prototyping iterations, and to improve transmission control algorithm and software quality. This paper will describe the application of this efficient approach to the development of a transmission control algorithm for production. The processes for algorithm design, closed-loop and rapid prototype testing, auto-code generation of production software, and potential hardware-in-the-loop verification are described with references to supporting development tools. This approach enables upfront, math-based development and performance assessment of transmission control algorithms and their interactions with other powertrain and vehicle control algorithms. Examples will illustrate the efficiency of the control algorithm development approach over a wide range of conditions.

Active Chassis Control Engineering with help from ITN/PD at DaimlerChrysler, has been developing a hardware-in-the-loop (HIL) system, for the evaluation and optimization of interaction among the various chassis control systems, and between the chassis control system and the vehicle. This HIL system consists of a transfer case, a hydraulic load box, two differential load boxes, an electronic control unit (ECU), a virtual 14-DOF (Degree of Freedom) vehicle model, and a computer system with a high-speed operating platform. The HIL system simultaneously demonstrates the advantages of both hardware testing and computer modeling. Different from conventional bench tester, the system offers the capability to implement dynamic ECU tests with feedback requirements for the sophisticated control algorithms, CAN diagnostics, fault injection, automatic-operating scenarios duplication and validation.

Active Chassis Controls engineering has been developing a hardware-in-the-loop (HIL) simulation system for electric control unit (ECU) testing, evaluating and optimizing the interactions among the chassis control algorithms, and between the chassis control systems within the vehicle. This HIL system consists of physical vehicle mechanical component simulators, an actual electronic control unit, and a virtual 14-DOF vehicle simulation model in a computer system with a high-speed operating platform and data acquisition capability. It simultaneously confers advantages of both hardware testing and computer modeling. Different from a conventional bench tester which lend itself better to testing static or state driven scenarios, the HIL allows testing of dynamic scenarios which require careful synchronization of major signals (such as vehicle speed, steering wheel angle, engine speed, yaw rate, and lateral acceleration, etc.).

DaimlerChrysler Activity Vehicle Engineering uses simulation to reduce algorithm development time, prototype iterations, and improve quality in chassis control systems. This paper describes the methodology and process of using simulation in the form of Software in the Loop, Rapid Prototyping, and Hardware in the Loop in the development of chassis control systems. The heart of the Activity Vehicle chassis control simulation is a 14 DOF vehicle dynamics model, which was developed using Matlab/Simulink/Stateflow®. This vehicle dynamics model represents the virtual vehicle in the Software in the Loop and Hardware in the Loop development stages. Control algorithms are also developed in Matlab/Simulink/Stateflow® and downloaded directly to a dSPACE® Rapid Prototyping system or to the production module via autocode generation using Targetlink®.