Model-based development and verification of control software for electric vehicles

Most innovations in the automotive domain are realized by electronics and software. Modern cars have up to 100 Electronic Control Units (ECUs) that implement a variety of control applications in a distributed fashion. The tasks are mapped onto different ECUs, communicating via a heterogeneous network, comprising communication buses like CAN, FlexRay, and Ethernet. For electric vehicles, software functions play an essential role, replacing hydraulic and mechanic control systems. While model-based software development and verification are already used extensively in the automotive domain, their importance significantly increases in electric vehicles as safety-critical functions might no longer rely on mechanical (fall-back) solutions. The need for reducing costs, size, and weight in electric vehicles has also resulted in a considerable interest in topics such as the consolidation of ECUs as well as efficient implementation of control software. In this paper we discuss two broad issues related to model-based software development and verification in electric vehicles. The first is concerned with how to ensure that model-level semantics are preserved in an implementation, which has important implications on the verification and certification of control software. The second issue is related to techniques for reducing the computational and communication demands of distributed automotive control algorithms. For both these topics we provide a broad introduction to the problem followed by a discussion on state-ofthe- art techniques.